Analysis Report on Cooperation vs. Investment Disputes from the

Analysis Report on "Cooperation vs. Investment" Disputes from the Perspective of Semantic Jurisprudence (Desensitized Reconstruction Based on DIKWP Model)

Yucong Duan

International Standardization Committee of Networked DIKWPfor Artificial Intelligence Evaluation(DIKWP-SC)

World Academy for Artificial Consciousness(WAAC)

World Artificial Consciousness CIC(WAC)

World Conference on Artificial Consciousness(WCAC)

(Email: duanyucong@hotmail.com)

Case Background and Focus of Controversy (Desensitized Restatement)

This report selects a typical civil capital contribution dispute for desensitized restatement. In the case, Funder A and Recipient B once participated in the operation of a project together: Party A provided substantial financial support to Party B, but the two parties did not sign a clear written agreement on the nature of this fund. After some time, differences arose in the project operation. A demanded the return of the capital contribution and obtain returns, but B claimed that the funds invested by A should essentially be borne by A along with the project's profits and losses. This triggered litigation, and the core controversy focused on: Does A's capital contribution behavior constitute part of Cooperative Operation, or is it a purely Investment/Lending relationship? Both parties held their own words: A tended to position the funds as Loan to ensure the recovery of the principal, while B claimed it was Investment Cooperation funds, implying responsibility for profits and losses without the need for return.

To protect privacy, we summarize the case process anonymously: A did not participate in the daily operation and management of B's company after providing funds. The two parties verbally mentioned "cooperation" dividends but did not agree on details of risk bearing. If recognized as a Partnership Cooperation Relationship, A should share profits and bear losses as agreed; if recognized as an Equity Investment Relationship, A as an investor does not guarantee the return of principal; if recognized as a Private Lending Relationship, B has the obligation to repay the principal and interest. The court of first instance supported A's claim for repayment and recognized the disputed funds as a loan. B was dissatisfied and appealed, changing the defense line multiple times (initially denying lending, then claiming the existence of a cooperative partnership, and then claiming the funds were investment for shares), but due to the lack of any partnership agreement or evidence of shareholder status, the court of final appeal still determined that there was no legal relationship of joint investment and operation between the two parties, and it belonged to private lending. The supreme trial opinion emphasized: Although there were "cooperation" words in the dealings between the two parties, "where there are only financial dealings but no facts of profit sharing and risk sharing, it should be recognized as a lending relationship rather than a partnership relationship." In other words, the core of the judgment in this case lies in clarifying the semantic nature of the capital contribution—whether it is a cooperative input or a lending investment. This focus reflects the cognitive dislocation in real civil transactions: the "cooperation" spoken in language may cover up the lending in law, and how to identify the essential semantics has become a difficulty in judicial adjudication.

In summary, the focus of the desensitized case is clarified as: Is the semantics of the funds provided by A to B "Cooperation" or "Investment/Lending"? This characterization relates to the rights and obligations of both parties: if it belongs to partnership cooperation, A needs to share risks; if it belongs to investment for shares, A is responsible for profits and losses and does not enjoy fixed returns; if it belongs to lending, A has the right to demand B to return the principal and interest. Next, we will introduce the "Data-Information-Knowledge-Wisdom-Purpose (DIKWP)" five-layer cognitive model to conduct a multi-level analysis of the semantic essence of this dispute, exploring possible paths for judicial adjudication to integrate multi-level semantic facts.

Ontological Analysis of Legal Concepts and Semantic Hierarchy Division

1. Semantics of Core Concepts:

Centering on the key legal terms "Cooperation," "Investment," and "Lending" involved in the case, we first sort out their traditional legal meanings: "Cooperation" (usually manifested as partnership or joint venture) means that both parties aim at joint operation, contribute capital together, share profits, and share risks; "Investment" generally refers to putting funds into other people's projects or enterprises to obtain future profits, where the investor needs to bear corresponding risks and the funds are not guaranteed to be returned; "Lending" is a typical creditor-debtor relationship, characterized by return of principal and agreed interest, where the lender does not participate in operation and does not need to bear operational risks. There are significant differences in the legal ontology of these three concepts: Cooperation/Investment belongs to equity input, where returns depend on operating conditions, and the law emphasizes the consensus of the parties and risk sharing; Lending belongs to creditor input, which has definite repayment obligations and guarantees.

2. Introduction to DIKWP Model:

DIKWP is a five-layer cognitive framework proposed by Professor Yucong Duan, which extends the classic DIKW hierarchy (pyramid) by adding the top layer "Purpose," forming a five-layer cognitive system of Data (Data)-Information (Information)-Knowledge (Knowledge)-Wisdom (Wisdom)-Purpose (Purpose). This model emphasizes driving the cognitive process with purpose, forming a closed loop from data perception to decision-making action. The semantic meanings of each layer are as follows: Data D: Record of original objective facts; Information I: Explanation imparting semantics and structure to data; Knowledge K: Higher-level laws and associations (forming a complete picture); Wisdom W: Ability to conduct high-order reasoning and decision-making by synthesizing knowledge; Purpose P: Motivation and goal layer, driving cognitive direction. The special feature of the DIKWP model lies in Networked Interaction between Layers: any two layers can provide bidirectional feedback, constituting 5×5 total 25 kinds of potential semantic transformation modules. This Networked Structure breaks the unidirectional flow of the linear pyramid, making the cognitive process more flexible, adaptive, and capable of self-correction. Simply put, DIKWP provides a multi-layer perspective for analyzing semantics, incorporating everything from the most specific facts to the highest-level intent and motivation into a unified framework for consideration.

3. Semantic Hierarchy Division Method:

Based on DIKWP, we attempt to restate the semantic levels of the facts of the case using labels such as "Same-Different-Complete" to discover the tension between traditional language descriptions and deep semantic judgments:

Data Layer (Same Points):

This layer extracts the Objective Facts that are undisputed by both parties as "same" data. For example, what can be confirmed as data in this case includes: A paid ¥X million funds to B via bank transfer in a certain month of a certain year; the funds were subsequently used for the expenses of the project controlled by B; during the fund transactions, both parties signed a "Settlement Sheet" stating that A had paid a cumulative total of ¥X million. These data layer facts provide a Common Starting Point for adjudication and do not change due to different subjective interpretations. The data layer does not involve semantic disputes, similar to the raw input perceived by a machine; it answers the question of "what happened."

Information Layer (Different Points):

Based on data, both parties endow facts with different semantic interpretations, forming Information Differences. That is, there is a divergence in understanding "what objective facts mean" by each party:

A's Information Perspective: A believes that the payment behavior is semantically equivalent to Lending Funds to B. Although they discussed cooperation, they ultimately did not actually form a partnership enterprise. Therefore, A claims that his payment was a lending behavior to obtain fixed returns and ensure principal safety.

B's Information Perspective: B interprets the same payment fact as A's Investment in the project, believing that A knew the invested funds were used for a joint project and there was a possibility of loss. The two parties initially had a verbal agreement on "cooperation dividends," so this money should be regarded as venture capital rather than debt.

It can be seen that "Same Data, Different Information" is the direct manifestation of the dispute in this case: a sum of money is Loan (Meaning: to be returned in the future) in A's eyes, but Cooperative Investment (Meaning: responsible for profits and losses) in B's eyes. The difference in the information layer stems from the different semantic frameworks selected by each party, corresponding to answering "what these facts mean."

Knowledge Layer (Completeness):

The knowledge layer requires us to place scattered information in a broader context to form a Complete Semantic Picture. That is, evaluating which interpretation is more grounded by combining legal rules and experience. In this case, the knowledge level includes: Did both parties sign a Partnership Agreement or articles of association to confirm A's shareholder/partner status? Did A actually participate in company management? Who bears the project operating income and losses? Around these key points, we integrated such a knowledge picture: ① No written partnership agreement exists: The two parties did not enter into a contract to clarify investment proportions, profit distribution, and loss bearing. ② A was not listed as a shareholder or manager: B company's industrial and commercial registration materials, project subcontract signing, etc., did not have A's participation or signature. ③ Income agreement and risk agreement are unequal: Evidence shows A was promised fixed return guarantees, but there was no agreement requiring joint assumption of project losses. ④ Use of transferred funds: After calculation, the funds transferred by A to B were mainly used for the advance payment of projects controlled by B and B's daily family expenses, not directly used for independent cooperation accounts. The above knowledge layer facts outline the Legal Context: According to civil and commercial law principles, Partnership Relationship usually requires an agreement clearly stipulating "joint investment, shared income, shared risk" and reflecting participation in management; while under Lending Relationship, the use of funds is irrelevant to operating results, and the core feature is fixed principal and interest, with risks entirely borne by the borrower. In the knowledge picture of this case, we see a lack of the risk-sharing mechanism that a partnership should have, and A actually acts as a fund provider whose input obtains a fixed guarantee commitment. Therefore, the complete analysis of the Knowledge Layer tends to support Lending Semantics: that is, judged by more comprehensive facts and rules, A's contribution behavior is more consistent with the characteristics of private lending. The knowledge layer answers the question "Overall, how to characterize the facts," equivalent to giving the complete contextual basis required for semantic judgment.

Wisdom Layer (Semantic Judgment):

The wisdom layer is the stage of value weighing and decision selection based on knowledge. In judicial adjudication, the wisdom layer is embodied as the ruling made by the judge after applying law and value trade-offs. As far as this case is concerned, after integrating data, information, and knowledge layer facts, the court used legal provisions and adjudication concepts to reason and formed the final judgment: "Considering that the two parties did not form a consensus on joint operation and risk sharing, the funds involved in the case should be characterized as a loan rather than cooperative investment." This wisdom layer decision balances legal stability and fairness considerations: Starting from maintaining transaction security, in the absence of explicit partnership agreements and where the funder obviously seeks capital security guarantees, protecting them as creditors conforms to common sense. The Supreme Court clearly pointed out that if the defendant claims the funds are a partnership/investment relationship, they need to provide evidence to prove the partnership agreement or shareholder status reaching a high degree of probability; conversely, as long as there is a lack of evidence of shared income, it should be inclined to find lending according to law. The adjudicative semantic path of the wisdom layer essentially condenses the "Semantic Conclusion" derived from the knowledge layer analysis: that is, the semantic essence of this case is a lending relationship. This layer answers the question "In terms of value and law, how should it be characterized and handled," equivalent to the embodiment of judicial wisdom.

Purpose Layer (Motivation and Purpose):

The Purpose layer further explores the Motivation and Purpose behind the actions of all parties. From the perspective of semantic jurisprudence, the purpose layer helps to understand the deep reasons triggering the dispute. In this case, A's Purpose is to obtain a safe and profitable investment channel—the reason he chose to "cooperate" with B was largely due to trust in B's project but also hoping to protect the principal from loss. This is a psychology of "wanting high returns but unwilling to bear equivalent risks." B's Purpose is to raise operating funds and minimize his own repayment obligations—B welcomes A's capital participation but does not want to give up control or bear repayment responsibility, hoping to position A as a risk-bearing investor. The inconsistency in the purpose layer of both parties foreshadowed the conflict: ostensibly both wanted to "make money together through cooperation," but A's hidden purpose was "sure profit without loss," while B's purpose was "borrowing a hen to lay eggs, transferring risks." When the project did not meet expectations, the misalignment of purposes led to the outbreak of semantic divergence: A insisted that he "did not intend to buy shares and share risks, but lent money to B," while B retorted "you clearly wanted to cooperate, but later regretted and demanded fixed returns." It can be seen that differences in the Purpose Layer intensified the tension in the Information Layer: when both parties contributed funds, they failed to clarify each other's true intentions and expectations. Although they said "cooperation" verbally, their inner expectations were inconsistent. This mismatch of purpose is the root cause why semantic tension is difficult to reconcile afterwards. Judicial adjudication usually does not directly recognize unwritten subjective intentions, but in discretion, it will consider whether one party has induced others to produce unrealistic intentions. For example, in this case, if B intentionally downplayed risks when accepting funds to make A believe there was a guarantee, it involves integrity issues. However, due to the lack of written evidence, the court mainly characterized based on objective facts (Knowledge Layer) and did not explicitly consider intention moral factors.

Through the above semantic hierarchy division, we see: Traditional Language Descriptions (such as "cooperating and investing together") often mask inconsistencies in multi-level semantics—the word "Cooperation" in surface language looks the same at the Data Layer (both say cooperation), but the understanding at the Information Layer is completely different. It must be corrected for its true meaning with the help of the Knowledge Layer, and finally, a legal judgment is made at the Wisdom Layer. The hidden divergence at the Purpose Layer of each party further exacerbates the tension between language and semantics. The tension between linguistic symbolic expression and deep semantic judgment is evident in this case: looking only at the literal and emotional aspects, A and B seem to "want to cooperate and do business together"; but looking at legal semantics, the relationship must be determined strictly according to the risk and return structure. The DIKWP model allows us to examine this tension in layers: under the same data, different information interpretations ultimately need to rely on a complete knowledge background, and judicial wisdom makes a meaning ruling that conforms to the actual contribution and risk-bearing situation of the parties.

Construction of DIKWP Cognitive Paths for Both Parties and Analysis of Semantic Tension Propagation

After clarifying the semantic levels, we further construct the DIKWP cognitive path maps for Funder A and Recipient B, analyzing how semantic tension is generated and propagated along layers in both parties' cognition, and how the court transforms and resolves these tensions in the adjudication path.

1. DIKWP Cognitive Path of Funder A:

Data D(A): The objective fact A sees is that he transferred ¥X million to B for a certain project. This data means to A that he has actually invested funds (paid quantifiable costs). A also retained some evidence as data, such as bank transfer vouchers, B's feedback on the use of funds in chat records between the two parties, etc. These data became the basis for A to build his claim.

Information I(A): Based on the above data, A's Information Interpretation of the event is: "I lent money to B." Although there was talk of cooperation initially, A's information processing chose a perspective beneficial to his own rights and interests. He noted that the two parties did not sign a formal partnership agreement, nor did they agree to bear losses, so he tended to think that his contribution should be understood as a kind of Loan (even if it was verbally called "cooperation" at the time, in his eyes it was just a way of saying to obtain fixed returns). From his side, B never let him participate in specific business decisions, which further strengthened his information judgment: he is a creditor rather than a true cooperative operator. A's information layer cognition also includes his understanding of risk—he always believed that the principal should be safe, otherwise he would not have contributed. Therefore, the information collected by A (such as the IOU B once wrote to him or the signature on the settlement sheet) was endowed with the meaning of "this is evidence of borrowing." It can be said that A's information processing path tends to interpret all facts as confirmation of a lending relationship.

Knowledge K(A): A formed a Cognitive Network supporting his claim at the Knowledge layer. He may have consulted legal professionals and learned: if there is no evidence to prove partnership, the court is more likely to find lending; also, there are cases from the Supreme People's Court indicating that "investment agreements that only agree on fixed returns and do not agree on loss bearing should be treated as lending." A incorporated these legal rules and case experiences into his own knowledge system as a basis for reasoning. This convinced him: he has Legal Basis to demand B to repay. At the same time, A's knowledge base also includes an understanding of B's behavior patterns—for example, he found that B often verbally said "cooperation" when raising funds from others but actually gave returns at a fixed interest rate. This background knowledge made him more convinced that his semantic understanding was correct. Through the integration of the Knowledge layer, A formed a Self-consistent Cognitive Structure: supported by facts (transfer vouchers), logical inference (no shared risk = lending), and legal basis (judicial interpretations and cases). This knowledge graph helped A develop arguments in court.

Wisdom W(A): At the Wisdom layer, A made an Action Decision: resort to law to demand B to repay the money and pay interest. A used the rules accumulated in his Knowledge layer to formulate a litigation strategy. For example, he chose to file a lawsuit through a Private Lending Dispute rather than a partnership dispute because he knew this was more favorable for the burden of proof. After winning the first instance, facing B's appeal and different defenses, A adjusted his strategy at the Wisdom layer: emphasizing points such as "fixed income, I did not manage operation" to defeat B's claim about cooperation. It can be said that A's Wisdom layer manifests as Rational and Purpose-Clear: aiming to win the lawsuit and get back the money, flexibly using legal knowledge, choosing the semantic path most favorable to himself (insisting on lending semantics). His decision also reflects value judgment: rather give up potential profits than risk principal safety. A's Wisdom layer cognitive output is finally reflected in the litigation request and logic of producing evidence.

Purpose P(A): A's deep purpose, as mentioned before, is Equal Emphasis on Financial Security and Returns. He was willing to contribute initially because he believed he could make a profit, but this intention always included an implicit premise: Principal cannot be lost. When he realized that partnership had no guarantee, his intention firmly became "take legal channels to protect himself." In the litigation stage, A's intention is also reflected at the psychological level: he expects the judge to Agree with his interpretation rather than be confused by the surface of cooperation. Therefore, in litigation, he may downplay the appearance of the word "cooperation" and constantly emphasize that he thought there was Loan Guarantee at the time. His subjective will may feel that he was deceived by B "borrowing the name of cooperation to practice borrowing," so the Purpose layer has a certain Sense of Deception and Determination to Seek Compensation. These intentions influenced his wording at the Wisdom layer, making him more inclined to emphasize his own good faith and the other party's breach of promise.

2. DIKWP Cognitive Path of Recipient B:

Data D(B): The objective data mastered by B is basically consistent with A: received ¥X million funds from A, funds were used for project and family expenses, and there is a fund transaction settlement sheet between the two parties. In addition, B also possesses some data: such as the profit and loss records of the project itself, recordings or text messages where A verbally expressed willingness to invest jointly, etc. These data constitute the factual basis of B's cognition. For B, every payment by A is data of "External Investment Injection," and he may have registered it as "So-and-so cooperation fund" or the like in the company accounts. These data provided a fulcrum for B's later defense.

Information I(B): B's Information Interpretation after semanticizing the above data is: "A became my partner investor." In B's eyes, A paying money to join the project naturally means accepting the risks of the project. Although the two parties did not write a detailed agreement, in B's information layer cognition, "A wants to make money with me, so he must also bear possible losses together." B's interpretation of the same settlement sheet, transfer vouchers, and other information is completely different from A: he would say these records prove A's investment amount in the project, not creditor transactions. In addition, B's information processing also includes his Understanding of A's Behavior: for example, A once participated in certain decision discussions or signed documents at the engineering site (even if just a signature), B emphasized these as information of A "participating in management as an investor." Even if A later denied management intent, B would insist that was the performance of a partner. In short, B chose a perspective of Reinforcing Cooperative Nature at the Information layer, bringing any ambiguous places closer to "cooperation": even a sentence like "do the project well together" in the chat between the two parties would be used by B to say this is information of a cooperation promise. B's Information layer is full of interpretations inconsistent with A, forming another set of event narratives.

Knowledge K(B): B formed a Knowledge Network supporting Investment/Cooperation at the Knowledge level. He may have also consulted lawyers or referred to cases to find grounds beneficial to himself. For example, he would cite the legal viewpoint that "Partnership contracts do not require a specific form," claiming that even verbal agreements can form a partnership as long as there is a fact of joint investment and operation. He may also cite previous court cases where investors' claims were rejected, showing that investment losses are not returned. In this case, B did indeed change strategies in different trials: emphasizing partnership relationship in the second instance, and claiming investment relationship in the retrial. This reflects that B is constantly adjusting at the Knowledge layer, hoping to find theoretical support recognized by the court. His knowledge base also includes some industry common sense: for example, not being listed in industrial and commercial registration does not necessarily prove not being a shareholder; some investments are anonymous, etc. B would even quote the verbal understanding of project profits and losses by both parties at that time—these belong to experiential knowledge. Through integration, B established such a knowledge chain: Fact of contribution + Act of participating in project + Agreement on income sharing (even if fixed) => Belongs to Cooperative Investment. Of course, this set of knowledge deviates from formal legal requirements, but B believes the judge might adopt it. He particularly firmly believes one point: "A clearly wanted to cooperate at first, but only changed his tune to ask for debt when he saw the situation was not good." Inferring from social common sense that a person would not give money for nothing, so he must want to make a profit and win-win, which in B's view is the inherent logical knowledge of partnership.

Wisdom W(B): At the Wisdom layer, the Response Strategy made by B is to fully argue against the lending characterization and emphasize Cooperation/Investment semantics to avoid the responsibility of immediate repayment. B's decisions include: denying lending consensus in the first instance, insisting that there was no loan contract between the two parties; changing tactics in the second instance, claiming that the original intention of both parties was to partner in business; and further adjusting to "A's money is actually investment money" in the retrial. These strategic shifts demonstrate the Probing and Weighing of B's Wisdom layer: he constantly looks for the most persuasive semantic position based on the feedback from the previous stage of judgment. For example, when the partnership defense lacked evidence, he changed to mention investment relationship, attempting to avoid the weakness of "unsigned partnership agreement" and focus on the use of funds and the nature of returns. B also made a series of Value Judgments at the Wisdom layer: he knew that if recognized as lending, he would immediately owe debt repayment, which was extremely unfavorable to him; if he successfully persuaded the court to recognize investment cooperation, at least he would not have to return the principal immediately, and A might have no right to claim due to losses. Therefore, he firmly chose any semantic path that might reduce his responsibility. This is actually a risk strategy game: exchanging a small probability for the possibility of debt exemption. B's Wisdom layer output is reflected in the focus of defense in court—constantly repeating keywords like "joint investment" and "agreed dividends," hoping the judge accepts this framework. His decisions also include evidence selection: for example, he would present witness testimony or WeChat records favorable to his position, even if these evidences are not sufficient, to create an impression of "both parties wanted to cooperate." In short, B's wisdom decision revolves around one goal: Transform the legal relationship towards the direction of cooperative investment to achieve the effect of exempting debt repayment or at least not processing it as lending.

Purpose P(B): B's fundamental purpose is Self-rescue through Financing and Maximization of Self-interest. From the beginning, his motivation for seeking A's funds contained the component of "Relieving financial pressure, but not wanting to increase debt." So he was more willing to use "cooperation" as a cover to obtain funds without being asked for fixed repayment. This initial intention determined his later firm stance of not repaying. During the litigation process, B's intention was also expressed emotionally: he might think A's "reneging" violated the tacit understanding of getting rich together at the beginning, thereby finding a moral excuse for his refusal to repay. His inner purpose lies in Persuading the court to accept his story—"A is an investor, investment has losses and wins, now that the project is not good, he wants the principal back, which is not in line with investment common sense." Such intention drove B to try his best in court to depict how both parties planned the project together at that time, and how A decided to contribute knowing the risks, etc. B's Purpose layer even contained the motivation to protect self-reputation: he did not want to be seen as a person who borrows money and does not repay, but preferred to be understood as a case of "entrepreneurial failure, investor withdrawal." Because the latter seems more acceptable in social perception. Therefore, B's attitude in the entire dispute was very determined to guide towards the semantics of investment cooperation. This force of intention made him not hesitate to repeatedly appeal, apply for retrial, and even use procuratorial organs to protest, all for one purpose: Maintain the interest structure where he does not bear debt.

3. Formation and Layered Propagation of Semantic Tension:

According to the above DIKWP paths of both parties, it can be seen that Semantic Tension is initially generated at the Information Layer (two different semantics of the same fund behavior) and transmitted upward through their respective cognitive chains. On A's side, the "Lending" interpretation of the Information Layer rises all the way, reinforcing into a closed loop where both Knowledge Layer and Wisdom Layer point to lending; on B's side, the "Cooperation/Investment" interpretation of the Information Layer is also solidified in his Knowledge and Wisdom Layer decisions. These two closed loops conflict with each other, forming the following tension propagation picture:

At the Data Layer, tension has not yet appeared: Both parties have no objection to the objective data that "transfer occurred," so they confirm this fact together in court, and data as a common basis has no conflict. However, this also means Tension lurks beneath the data—because any subsequent differences revolve around the interpretation of these data.

At the Information Layer, tension appears suddenly: A's information output is "this money = proof of loan," and B's information output is "this money = investment participation." This is the source point of tension, The same fact is endowed with different meanings. Both parties were tit-for-tat from the beginning in court, each sticking to their own version. At this time, semantic tension manifests as "Semantic Rupture": language may both mention words like "contribution" and "cooperation," but implied definitions differ. For example, "cooperation" in B's mouth means dividends without guaranteed principal, while "cooperation" in A's mouth may be just polite talk actually requiring guaranteed principal. If this Information Layer rupture is not resolved, it will directly lead to adjudication difficulties.

At the Knowledge Layer, tension further intensifies or attempts to bridge: Both parties mobilize legal and factual knowledge to prove that their interpretation is complete and correct. A brings out legal provisions and cases to prove that without risk agreement it should be treated as lending, while B cites so-called facts of cooperation between parties and investment characteristics attempting to cover the other party's argument. Here tension manifests as "Non-overlapping of Cognitive Graphs": A's knowledge graph and B's knowledge graph have almost no intersection, and are even diametrically opposed. For example, the matter of "fixed income," in A's knowledge system = evidence of lending, in B's knowledge system = merely a way of agreeing on investment returns; "unsigned agreement" in A's view = no basis for partnership, in B's view = implied partnership is still possible. This conflict of knowledge where everyone talks past each other challenges adjudication: the court must choose one of the two incompatible cognitive frameworks, or reconstruct a third framework to interpret the facts.

At the Wisdom Layer, tension transforms into adjudication choice: Finally, the judge cannot simply reconcile the views of both parties, but can only choose one semantic path and give sufficient reasons, Transforming tension into Adjudication Semantics. In this case, after deliberation, the court adopted the cognitive path of party A as the basis, i.e., lending semantics, and detailed why it did not recognize cooperation but recognized lending through the "Court's Opinion" part of the judgment. In this process, the tension in Information and Knowledge layers is Transformed: the court ends the dispute with the authoritative determination of Legal Semantics. For example, the Supreme Court determined: "The two parties did not constitute a partnership relationship of joint contribution and shared profit and loss... it should be a private lending relationship." This sentence actually dissolved the double meaning of the Information Layer and determined a single semantic—even if you verbally say cooperation, legally I see it as lending. The judgment of the Wisdom Layer is equivalent to a Unilateral Cut on tension: fixing one interpretation and discarding the other. For the winning party (A), the tension is eliminated; for the losing party (B), the tension is "resolved" in the form of damaged interests.

At the Purpose Layer, tension may still lurk undecided: It is worth noting that the judgment did not truly reconcile the subjective intention divergence of both parties, but only biased towards one party in terms of legal results. A achieved his purpose (recovering funds), while B's purpose failed. The tension in the Purpose Layer (mismatch between psychological expectations and results of both parties) will not completely dissipate because of the judgment, and may transform into dissatisfaction of one party or application for judicial relief (as in this case, B applied for procuratorial supervision protest after the judgment). This reminds us: Legal adjudication solves semantic conflicts at the objective level, but tension at the subjective Purpose level is sometimes difficult to quell and needs to be relieved through mediation or other means.

4. Tension Transformation in Court Adjudication Semantic Path:

When dealing with such semantic disputes, the court actually has to complete an Integration and Transformation of Semantic Paths. The judge is equivalent to constructing his own DIKWP cognitive route:

Data Layer: Adopt data undisputed by both parties (fact of contribution, etc.);

Information Layer: Identify conflicting information points stated by both parties (Loan vs Investment) and distill the focus of dispute;

Knowledge Layer: Mobilize legal regulations and evidence to verify disputed information. In this case, the court's knowledge layer work involves examining facts such as whether there is a partnership agreement, use of funds, income and risk arrangement, and comparing with relevant legal standards, such as Article 16 of "Provisions on Private Lending," elements for identifying partnership contracts, etc. In this process, the court actually constructs Its Own Knowledge Graph, the content of which integrates information submitted by A and B as well as legal norms, forming a relatively comprehensive and neutral cognitive framework.

Wisdom Layer: Based on this knowledge framework, the court makes value judgments and legal applications, drawing conclusive opinions. For example, believing that maintaining transaction security and preventing debt evasion should incline towards lending characterization; while considering that evidence is insufficient to prove the existence of partnership. Thus, the court's Wisdom Layer semantic path converges with A's path: the two are consistent in conclusion, only the court needs to give more objective rationale. Tension in Information and Knowledge layers is "digested" in the court's Wisdom Layer: the judge transforms subjective disputes into objective questions by citing objective standards (such as whether there is a written agreement, whether there is a record in the register of shareholders, etc.), thereby dissolving pure semantic differences.

Purpose Layer: The court's Purpose (Purpose) lies in realizing fairness and justice and maintaining the authority of the rule of law. Specifically in this case, it is to find a balance between maintaining the spirit of contract and protecting the interests of investors. The Supreme Court's judgment this time obviously intends to Regulate expectations for similar disputes: reminding financiers not to abuse the name of "cooperation" to evade repayment, and also reminding investors that if they want to cooperate, they should agree clearly, otherwise the court will adjudicate based on the substance of the transaction. This judicial intention guided the tone and reasoning of the judgment, making the judgment not only solve individual cases but also transmit rules. Similarly, the court's Purpose Layer also focuses on social effects, striving to quell the parties' dissatisfaction through sufficient reasoning—for example, detailing why B's claims are untenable to block space for re-argument.

5. Detection of Tension Broken Links and Semantic Backtracking Explanation:

Aiming at the above adjudication path, we can establish a "Tension Broken Link" Detection Model to examine whether the semantic interpretation of the adjudication is comprehensive and interpretable: simply put, it is to check whether the court has responded to and converted the main views of both parties at each level, avoiding unexplained faults in the logical chain. If a key dispute is not responded to in the judgment, a "broken link" is formed, weakening the persuasiveness of the adjudication. Applying this model to backtrack the semantics of the judgment in this case:

Information Layer Broken Link Check: Has the court explicitly addressed the core information divergence of both parties—the nature of the funds? The answer is yes. The judgment opens by summarizing the focus of the dispute as "Lending Relationship or Partnership Relationship." This indicates that the court fully identified the tension in the Information Layer and did not avoid talking about it. The risk of broken links is lifted at this layer.

Knowledge Layer Broken Link Check: Has the court commented one by one on the main factual basis and legal claims raised by both parties? In the judgment, the court discussed why the cooperative relationship claimed by B was untenable: no partnership agreement, no evidence proving A was a shareholder or manager of the company, several documents signed by A were insufficient to prove partnership status, etc. It also emphasized how the settlement sheet and use of funds submitted by A proved the lending relationship. These show that the court Responded to evidence and arguments of both parties at the Knowledge level, incorporating them into its own cognitive framework for evaluation, rather than just giving a conclusion. This item-by-item response makes the knowledge chain complete, leaving no party's argument hanging. For example, B might claim "the settlement sheet does not reflect interest deduction, indicating it is not a loan," and the court also explained in the judgment that "failure to offset debt does not affect the determination of debt nature," which exactly blocked the breach B tried to open in the knowledge chain. It can be seen that the court's adjudication logic is basically Closed at the Knowledge Layer, leaving no obvious broken links.

Wisdom Layer Broken Link Check: Are the final conclusion and reasoning process smoothly connected? The court's conclusion is private lending, which is in line with the previous fact-finding and legal analysis. The argument in the judgment lists facts first, then applies the law, and finally makes a judgment on nature naturally. Readers can clearly understand the court's thinking from elements (presence of three elements of partnership) to conclusion. The Wisdom Layer did not suddenly jump to a conclusion or introduce new unproven factors. In this way, the interpretability of the adjudication is well established—anyone backtracking the judgment semantic path can find that the conclusion "Lending Relationship" is the natural result of previous analysis, not an arbitrary decision.

Purpose Layer Broken Link Check: Is there an explanation for the court's value trade-off? Although the judgment mainly argues at the fact and law levels, the value orientation contained behind it can be interpreted, that is, prioritizing the protection of the funder to prevent dishonest behavior of fake cooperation and real lending. The Supreme Court's protest trial upheld the original lending characterization, implying that it considered the importance of maintaining transaction order. Although the judgment did not directly say "this case is judged as lending to prevent the financier from escaping debt," this intention is reflected in the judgment reasoning as an emphasis on the requirement of risk sharing. Therefore, the Purpose Layer is not without trace. For the parties, A certainly read the intention of judicial protection for him, and B also felt the judicial disapproval of his behavior of evading responsibility. There is no "break" at this level, only that the judge's intention is not as explicit on paper as data and law, but careful analysis can understand its meaning.

Through the inspection of the "Tension Broken Link" model, we confirm that the adjudication of this case is Coherent and Self-consistent in semantics: the court identified and responded to key disputes at all levels, converted different semantics of both parties into its own adjudication semantic chain layer by layer, and finally gave a justified conclusion. Such a judgment has high interpretability and persuasiveness semantically. By contrast, if the court omitted any layer (e.g., only concluding "belongs to lending" without explaining why it is not a partnership), it would create a semantic broken link, causing the parties to be unconvinced and even triggering continued appeals. In AI-assisted trial models, this broken link detection idea can also help the system review whether the output legal reasoning process is complete, which has positive significance for improving the interpretability of AI judgments.

Value Modeling of Wisdom Layer Contribution and Non-traditional Capital Contribution

This case reveals a deep problem: traditional justice often Focuses on the determination and protection of Monetary Contribution, while lacking evaluation mechanisms for the parties' inputs in wisdom levels such as information, knowledge, and purpose. One party may have invested non-monetary "soft assets" such as intelligence, creativity, and management. These Wisdom Contributions are of great value in cooperative relationships, but once the law characterizes it as lending or investment failure, the provider often receives no compensation. To fill this gap, we attempt to construct a value evaluation system for non-traditional contributions based on the DIKWP model and propose the concept of "Semantic Compensatory Justice", transforming wisdom contributions into a quantifiable value structure, aiming to be considered in adjudication.

1. Non-monetary DIKWP Contribution Dimensions:

According to the five layers of DIKWP, we can divide all inputs of parties in a cooperation/investment relationship into different levels of contribution types:

Data Layer Contribution: Providing original resources or data. Such as providing market information, customer lists, technical parameters, etc. Although not directly funds, they belong to basic input, laying a factual foundation for cooperation. For example, A might have provided his own network resources or project information in the early stage of the project, which is a typical Data Layer contribution (information material).

Information Layer Contribution: Providing meaningful intelligence, analysis, or suggestions, processing raw data into useful information for the project. For example, offering advice, business intelligence collection, etc. In the context of this case, assuming A had done a feasibility analysis report or marketing plan for the project, even if he did not actually manage, this behavior is an input at the Information level, improving project awareness.

Knowledge Layer Contribution: Contributing systematic experience and professional knowledge, including technical know-how, management experience, business models, etc. For example, if A possesses professional knowledge in a certain field and uses it for project decision-making, then he has invested assets in the Knowledge Layer. This is similar to the concept of "Technology Shares," that is, contributing capital with technology and intellectual property rights. Knowledge layer contributions are often crucial to project success, and their value may not be less than capital investment.

Wisdom Layer Contribution: Participating in high-level decision-making, strategic planning, innovation and creativity belongs to Wisdom Layer contribution. For example, A assisted in formulating project strategies, making key decision judgments, and solving major problems. These reflect the promotion of his wisdom to the cooperative cause. Such contributions are usually difficult to quantify but have a profound impact on results, equivalent to the value created by advisory or leadership roles.

Purpose Layer Contribution: This dimension is relatively abstract, referring to the contribution of Will Synergy and Credit Endorsement. One party's sincere investment in cooperation willingness, persistence in common goals, and the help of their own reputation for project financing or credibility all belong to Purpose Layer contributions. For example, A's participation itself makes the project more credible (his fame attracts resources), or A shows strong responsibility and loyalty in cooperation, promoting team cohesion. These intangible contributions are hard to measure but indeed increase the probability of project success.

Using the above dimensions, a "DIKWP Contribution Spectrum" can be constructed: rising step by step from specific data-type contributions to abstract purpose-type contributions. Traditionally, courts only recognize tangible contributions such as physical objects/funds, but in many cooperation disputes, what the parties dispute are also those soft contributions paid but not rewarded. For example, one party invested a lot of time and energy to run the company but had no way to claim compensation because they did not become a formal shareholder. The perspective of Semantic Justice believes that these should all be regarded as inputs in the cooperative relationship, only with differences in semantic levels.

2. Semantic Weight Assessment System:

We can try to assign certain Weights to contributions at different levels to assess the comprehensive contribution value of each party in cooperation/investment. This needs to consider factors such as contribution type, impact on project success or failure, replaceability, etc. Examples are as follows:

Data Contribution: Weight is relatively low because data is easy to obtain and highly replaceable, unless it is exclusive important data. For example, key market information should also increase weight once the impact is significant.

Information Contribution: Assessed based on information uniqueness and value gain. The value provided by general intelligence can be converted into reduced trial and error costs or increased success probability for measurement. For example, market analysis provided by A allows the project to avoid wrong directions, which can be converted into saved costs = value.

Knowledge Contribution: Weight should be higher, especially for technology-driven projects. The contribution of a core technology or patent can be valued based on its share of earnings for the project. If there is no patent, knowledge experience can be measured by market price (expert consultation fees, consultant salary) substitutes. For example, A's professional knowledge is equivalent to hiring a senior consultant, with a monthly value of ¥N, which can be calculated cumulatively.

Wisdom Contribution: Value assessment at this layer is the most difficult, but Decision Value Quantification methods can be adopted: analyze the impact of key decisions on project NPV (Net Present Value). If a strategic decision by A made the project earn an extra 1 million, then this 1 million gain can be attributed to his wisdom contribution. In addition, innovation and creativity can be quantified by considering intellectual property or commercial value. For example, how much the business model he designed was later valued. This requires semantic causal derivation to attribute part of the result to that wisdom contribution.

Purpose Contribution: The value of purpose and credit can be reflected through project Financing Premium or Team Stability. For example, because of A's participation, the project raised an extra 5 million, or team morale improved leading to efficiency enhancement, these effects can be converted into monetary value. The value of credit endorsement can also be calculated through brand appreciation, etc. Although this is subjective, some models like Influence Index can assist in assessment.

Through such weighted assessment, the Total Contribution Value of each participant =  Σ ( contribution of each layer × weight × influence coefficient ) . Taking A as an example, assuming: Data contribution 5 points, Information contribution 10 points, Knowledge contribution 20 points, Wisdom contribution 15 points, Purpose contribution 10 points (weights have integrated influence), then A's total contribution = 60 points. While B might have greater contribution in Knowledge and Wisdom layers (being the leader after all), his contribution value might be 80 points. Then looking at capital investment, A invested X million funds, B invested technology and labor converted to Y million, thus a More Comprehensive Contribution Comparison can be obtained.

3. Value Transformation Mechanism Design:

When a dispute arises, if the court only considers funds, then A can only get back the principal and interest, and B gets nothing if his labor effort fails. But Semantic Compensatory Justice advocates: mechanisms should be established to appropriately Transform the above contribution value differences into Compensation or Rights to achieve fairness.

One design idea is: introduce "Quantified Contribution Coefficient" to adjust compensation during adjudication. For example, if it is determined that this case is indeed a lending relationship, but B provided a large amount of wisdom labor (e.g., B put huge efforts into operation), the court can adjust interest or liquidated damages at its discretion within the statutory range to compensate B's non-monetary payment. Conversely, if recognized as a cooperative relationship but A invested little intelligence and only money, then A's funds should mainly be returned during liquidation, and B gets less money, because B's main contribution was losing labor but creating no profit, and should not pay extra.

Specifically, there can be the following mechanisms:

Contract Agreement Priority Mechanism: Encourage parties to clarify their respective non-financial contributions and compensation methods in case of disputes in the agreement. For example, agree that if cooperation terminates, the funder pays the manager a certain compensation, or the technology contributor is compensated according to a certain valuation. This solidifies semantic value at the contract level first, and the court executes according to the agreement.

Quantified Compensation Rules: Add clauses in the law, such as "Inputs (including labor, intellectual property, etc.) made by cooperation parties for common affairs can be valued and counted as capital contribution according to agreement or statutory standards. When the cooperative relationship is dissolved, appropriate economic compensation can be given by the beneficiary for non-monetized inputs." In this way, even if not agreed, the judge has a basis to give at discretion.

Liquidation Proportion Adjustment: If ultimately treated as partnership or investment, profit and loss need to be liquidated. It seems unfair to stipulate that losses are entirely borne by the funder, because the other party did not invest money but invested wisdom. The concept of "Wisdom Capital Contribution Offset" can be introduced: when allocating losses or remaining assets, first calculate the comprehensive contribution proportion of each party, then bear or share proportionally. Example: A's capital contribution accounts for 60%, B's wisdom contribution accounts for 40%, then profits are distributed 6:4, and losses are also shared 6:4, instead of generally A bearing all principal losses. In this way, B's input (wisdom, etc.) is recognized in the calculation, and even if he did not take out cash, it is equivalent to bearing 40% of the loss.

Litigation Relief Channels: If the court cannot directly compensate wisdom contribution under current laws, consider giving through Unjust Enrichment or Principles of Fairness. For example, assuming the opposite scenario in this case: if the court determines that cooperative investment caused A's principal loss and no right to claim back, but A indeed made major wisdom contributions benefiting B, at this time A can sue separately demanding B to return unjust enrichment or give compensation, on the grounds that A's wisdom input benefited B without remuneration. The court can support part of the compensation appropriately based on the principle of fairness. This is similar to the application of Culpa in Contrahendo and Fair Liability systems in civil law systems, compensating losses that cannot be claimed through the main contract via incidental legal responsibilities. Semantically, it acknowledges that part of A's value contribution was not reflected in the liquidation of partnership failure, and it is unfair for B to appropriate it all, which needs correction.

4. Significance of "Semantic Compensatory Justice":

Through the above value modeling and mechanisms, judicial trials can more comprehensively reflect the Value of Multi-level Inputs of parties. This has the following benefits:

Prevent Unjust Enrichment by One Party: In reality, in many disputes, one party invests a lot of human and intellectual resources, and the other party suddenly withdraws or the contract is invalid, causing the former to get nothing or even worse. Quantified compensation can avoid letting one party work in vain. For example, in this case, if standing from B's perspective, if the project fails and he still has to repay principal and interest, wouldn't it mean all his labor efforts return to zero and he pays extra? If B indeed has huge efforts difficult to measure in money, the law can reflect this by reducing his payout amount, making responsibility allocation more balanced.

Encourage Honest Cooperation: Parties will be more willing to list frankly and perform these inputs seriously only when they know their various inputs have value in law and will not be ignored. Otherwise, worrying "I do it in vain," they might slack off or hide information. Semantic compensation makes "Wisdom also have a price," improving cooperation enthusiasm and trust.

Maintain Moral Fairness: Justice is not only about calculating economic accounts but also conforming to reason and morality. Recognizing non-monetary contributions reflects the law's respect for labor and creativity, preventing those who exploit legal loopholes from using others' wisdom and then denying it. For example, if B loses the lawsuit completely and pays back money, but some project achievements actually rely on his efforts, it is unfair for A to profit from others' toil. With wisdom compensation consideration, the judge can state in the verdict that the contributions of both parties have been considered, thereby letting the losing party also feel the fair treatment of the procedure.

Promote Institutional Innovation: In the long run, emphasis on the value of non-traditional contributions can promote the improvement of legislation or judicial interpretations. For example, Special Handling Rules for "Cooperative Investment" Cases can be established, specifically regulating how to identify and settle various types of contributions, including labor contributions, knowledge contributions, etc. Currently, Company Law and Partnership Enterprise Law have provisions on intellectual property contribution valuation, but the scope of application is limited, and it is still a gray area in non-corporate cooperation. Semantic justice models can serve as a basis for policy recommendations, promoting the writing of these flexible compensation mechanisms into legal provisions.

It needs to be emphasized that "Quantification of Wisdom Contribution" does not encourage arbitrary expansion of compensation, but serves as a reference consideration Only when there is basis and need for fairness. Because excessive subjectivity may bring judicial uncertainty. Therefore, in practice, objective standards and expert assistance mechanisms (such as hiring accountants to assess the value of knowledge assets) should be established to quantify as accurately as possible. This is also where the DIKWP model plays a role—using knowledge graph and semantic network technologies to associate intangible assets with the utility they bring, providing a basis for quantification.

In short, through the DIKWP framework, we clearly define contributions such as wisdom and information traditionally hidden behind language as Semantic Level Assets, and design corresponding Value Assessment and Compensation Mechanisms. This introduces a new perspective of equity consideration for civil justice, promoting dispute resolution from "Calculating Accounts" to "Calculating Wisdom," thereby more comprehensively realizing substantive justice.

Multi-agent Semantic Interaction Analysis under Networked DIKWP*DIKWP Model

Single disputes often involve the cognition and interaction of multiple agents. To further expand, we adopt the "Networked DIKWP*DIKWP Model" to view the court, parties, hearing experts, and other agents as DIKWP systems, and analyze how these systems nest and interact, how semantic paths intersect, and how tension is reconciled and closed under multi-party synergy.

1. Definition of DIKWP*DIKWP Model:

"DIKWP*DIKWP" can be understood as the Cartesian product or coupling network of multiple DIKWP systems, that is, each agent has its own Data-Information-Knowledge-Wisdom-Purpose link, and these links form a larger network through interaction. In the scenario of this case, at least three-party agent DIKWP systems are involved: A's DIKWP, B's DIKWP, and the Court's (Judicial Organ) DIKWP. If considering the hearing expert group that may be held before trial, they also constitute one or more DIKWP (Group Cognitive Systems). The networked model means that these systems are not simply connected in series, but nested and multi-directionally fed back to each other. For example, the cognition of A and B will affect the judge's cognition through litigation confrontation (input into the Data Layer of the judge's DIKWP), and at the same time, the judge's words and tendencies in court will feedback and affect the strategies of A and B (change their Information/Wisdom Layer decisions). For another example, the opinions of hearing experts will act on the court's Knowledge Layer, and the court's questions will also guide the experts' focus. This multi-Agent cognitive interaction can be viewed as a networked extension of the DIKWP system.

2. Agent Model Nesting:

Viewing each agent as a subsystem, a nesting relationship diagram can be constructed: Court DIKWP is at the outer layer, responsible for integration and adjudication; A and B's DIKWP are located within it as information sources; the expert hearing can be seen as a middle layer DIKWP between the parties and the court, acting as information filtering and knowledge supplementation. Specifically:

Court DIKWP Outer Layer System: The Data Layer acquires evidence materials and statements submitted by both parties A and B (these data essentially come from the output of A and B's Wisdom Layer); the Information Layer is the court's preliminary summary of the facts of the case (integrating data provided by parties into "case information"); the Knowledge Layer mobilizes legal norms and case experience to understand disputes; the Wisdom Layer makes judgments and rulings; the Purpose Layer contains the court's goal of pursuing fairness and justice and maintaining the rule of law. The court system almost uses A and B systems as "senses" and law as "brain" to form a complete closed loop.

A's DIKWP Subsystem: Detailed before, not repeated. The key is that A system will apply its own output to the court system: A submitting evidence and claims to the court is equivalent to inputting its own Information/Knowledge Layer products into the court's Data Layer. A's intention (winning the lawsuit) may even adjust after perceiving the court's tendency, which manifests as the reaction of the court system to the A system—e.g., the judge's question in court made A realize a certain deficiency, and he went back to supplement evidence, this is the court's feedback in Knowledge/Wisdom layer affecting A's behavior in Data/Information layer.

B's DIKWP Subsystem: Similar to A, also bidirectional interaction. B providing defense materials to the court is equivalent to providing his cognitive content to the court system's Data Layer. If the judge questions B's certain point in court, B will adjust statement or add materials at Information/Wisdom layer, which is also a manifestation of cross-system feedback.

Expert Hearing DIKWP System: Hearings are usually held during procuratorial protest review or court retrial review, inviting legal experts or third parties to discuss the case. It can be viewed as a collective DIKWP: Data layer is case materials, Information layer is experts' respective insight speeches, Knowledge layer is legal provisions and experiences cited by experts, Wisdom layer is manifested as tendentious opinions or suggestions after expert group discussion, Purpose layer is the starting point of maintaining fairness and improving case handling quality. In this case, it is recorded that the Supreme Procuratorate held a hearing discussion on this case, and some experts believed it should be treated as a partnership. This means the Expert DIKWP system output a Wisdom conclusion different from the court's first and second instance (leaning towards cooperation semantics). This output (protest opinion) entered the Data Layer of the Supreme Court DIKWP, making the Supreme Court have to consider the challenge of another cognitive framework. In court, members of the collegiate bench of the Supreme Court can also be seen as a small DIKWP group, exchanging information and knowledge through deliberation, and finally forming a unified Wisdom output.

3. Semantic Path Intersection Points:

In multi-agent interaction, some nodes are key Semantic Intersection Points, where information flows of different DIKWP systems collide and dock:

Complaint/Defense Stage: A submits the complaint, B submits the defense, this is the First Semantic Frontal Intersection between A system and B system, and also the starting point of exposing differences to the court. When the court reads these materials, the semantic paths of A and B appear side by side in the judge's mind, forming a contrast. This intersection is extremely important for the subsequent direction: the court establishes a preliminary semantic framework for the case at this time—if it is unclear, the judge may request supplements. If A and B's views are diametrically opposed, the judge will set up issues. It can be seen that Information Layer Tension is captured at this intersection point, and the court determines the focus of the dispute accordingly.

Court Cross-examination Stage: This is a typical multi-system real-time intersection. A and B question each other and submit evidence in court, responding to each other's claims on the spot. The judge questions and guides in the middle. At this time, three DIKWP systems interact almost Synchronously: A and B constantly project their respective information/knowledge flows to the other party and the judge, and the judge instantly feeds back his own knowledge (legal provisions) and information (questions) to both parties. For example, the judge asks B: "Do you have evidence to prove A participated in dividends?" B might look up materials or answer no on the spot. At this moment, the link Court Knowledge Layer -> B Data Layer is formed, directly affecting the subsequent output of B system. Similarly, B's answer becomes court data again. This high-frequency intersection fully exposes semantic tension and also creates conditions for resolving tension—because misunderstandings can be clarified through cross-examination, and facts can be confirmed or denied on the spot.

Expert Hearing: If a hearing is introduced before the formal judgment, a intersection of Court DIKWP and Expert DIKWP is generated. In the public hearing hosted by the procuratorate, the discussion results of experts will be input into the Wisdom Layer of the procuratorial organ DIKWP as Information/Knowledge to decide whether to protest; if protested to the court, the expert opinion becomes one of the factors considered by the court's Knowledge Layer. The Supreme Procuratorate adopted expert opinions to protest in the hearing of this case, directly influencing the Supreme Court to accept the retrial. This is a significant intersection of semantic paths: Expert System Output (Cooperation Semantics Suggestion) -> Procuratorial System Wisdom Layer (Decide to Protest) -> Court System Data Layer (Protest Letter). Although the court ultimately did not accept cooperation semantics, this process ensured that before making a wisdom judgment, the court was exposed to full discussion of different semantic frameworks, increasing the rationality and objectivity of the adjudication.

Collegiate Deliberation: Inside the court, members of the collegiate bench are also DIKWP individuals, and their understanding of the case may differ. At the deliberation meeting, judges exchange views, which is Multi-DIKWP Intersection Inside Court. If the undertaking judge leans towards lending while another judge leans towards cooperation, they will debate evidence and legal application. This is similar to expert hearing, only conducted internally in the court. Through this intersection, the court internally reaches a consensus semantic path and finally issues a judgment with a unified voice. This link ensures the Closed-loop Synergy of adjudication semantics: different views are merged into one through gaming, making the judgment more robust.

4. Tension Reconciliation Mechanism:

In multi-agent networked interaction, semantic tension can be reconciled or alleviated through several mechanisms:

Information Symmetry: Through intersection interaction, make each agent master as much identical information as possible, thereby reducing semantic conflicts caused by inconsistent information. For example, court cross-examination allows A and B to share each other's evidence, and expert hearings allow third parties to also master all case details. This Improves Data Layer Consistency, laying the foundation for reconciliation. The more transparent the information, the more substantive the dialogue, and the possibility of tension resolution exists.

Semantic Calibration: The host (judge, hearing host) plays the role of Semantic Ordering. They can Calibrate Discussion Focus through summary and questioning, avoiding talking past each other. For example, the judge summarizes: "The dispute lies in the nature of the funds, please both parties express opinions focusing on risk bearing." This guides both parties' semantic paths to the same issue coordinate, reducing tension on diverging paths.

Third-party Assessment: Experts, mediators, etc., as relatively neutral DIKWP, can give objective comments or compromise plans on the semantics of both parties. For example, an expert might point out: "According to business practice, if there is no written agreement, mostly it should be recognized as lending," but also remind A to understand that B as an operator also put in effort. This objective evaluation on one hand may persuade B to accept reality (lowering his psychological tension), and on the other hand prompt A to consider giving in (such as giving up part of the interest as care for B's labor). The third-party DIKWP acts as a Buffer Layer for tension, transforming sharp conflict into rational discussion.

Purpose Docking: If parties can be made to frankly exchange understanding of each other's intentions, it helps eliminate misunderstanding and hostility. For example, at the hearing, it might be asked: "A, if the project loses money, are you really willing not to want a penny?" A might answer unwilling, then the expert can question that he didn't completely consider it as lending initially. Then ask B: "If it was said at the beginning that principal would be returned even if lost, would A still pay?" B might admit no. Such dialogue makes both parties Realize that each other's intentions were misplaced at the beginning, thereby understanding why the other party sues like this. Although the law cannot satisfy both intentions, reconciliation in emotion and understanding helps accept the ruling. In other words, Communication at the Purpose Layer can reduce resistance when enforcing judgments.

Closed-loop Synergy: Ideally, through the above mechanisms, the multi-agent system can form a Synergistic Closed Loop: parties gradually adjust their cognitive paths in communication, move closer to each other, and finally reach consensus or compromise on key semantics, thereby resolving disputes on their own or clearing obstacles for adjudication. This is somewhat similar to "consensus formation." In justice, this manifests as Successful Mediation or Parties Accepting Judgment and Ceasing Litigation. For example, if most experts support lending in the hearing link, B may realize that the chance of winning is slim and negotiate with A, and both parties reach a settlement, each taking a step back. This is closed-loop synergy: the intentions of all DIKWP agents point to settling the dispute as soon as possible, so they adjust their respective wisdom decisions to reach agreement. Conversely, if synergy cannot be achieved (like B in this case still refused to accept after protest failed), then the closed loop can only be realized by external force such as enforcement, which is not true semantic synergy, just forced calming.

5. Outlook of Closed-loop Synergy of Networked Model:

Through DIKWP*DIKWP modeling, we can imagine an optimized dispute resolution mode: effective integration of cognitive paths of various agents. Future smart courts or mediation platforms can play the role of "Super DIKWP Coordination System", collecting and analyzing semantic expressions of parties and experts in real time, finding divergence points and giving feedback suggestions. For example, the system reminds: "Both parties have different understandings of the word 'risk', please clarify," or "According to the legal knowledge graph, your claims can seek a middle solution on point XX." Such AI assistant is equivalent to adding a global observation node in the networked model, helping humans reconcile semantic tension. Finally, the ideal closed-loop mode is: parties' intentions converge (both want to solve disputes fairly), information and knowledge are shared fully, adjudicator wisdom is authoritative and fair, semantic flow of the whole system is smooth and unimpeded, and tensions at all layers are identified and handled when formed, so as not to intensify to an unmanageable level.

Although this case failed to settle outside of litigation, the multi-agent interaction reflected in its process has already demonstrated certain synergy: for example, the error correction and supervision function played by procuratorial organs, the integration of expert opinions, etc. This shows that under the networked DIKWP model, different agents can jointly promote the case towards fact clarification and accurate characterization through semantic interaction within their respective roles. Even if opinions differ in the end, adjudication by the court in the middle is also a way for the networked system to seek a closed loop (forcibly closing the loop with judicial authority). This convergence from multi-source cognition to a single conclusion is essentially a self-organization process of the semantic network.

In summary, the Networked DIKWP*DIKWP Model allows us to see that the trial activity between the court, parties, and experts is actually a Semantic Synergy Network: information flows and transforms between different cognitive bodies, and conflicting semantics are constantly parsed and anchored through interaction. When this network operates efficiently, and nodes communicate frankly and think according to law, it is more likely to reach a trial of "Semantic Consistency", forming a consensus or accepting the result of co-judgment at the factual and legal levels. Conversely, if the network is blocked somewhere (such as one party refuses to communicate or conceals information), the semantic closed loop is difficult to form, and can only be balanced by external force, then the resolution will not be satisfactory. The inspiration of the networked model is: judicial procedures should be designed as much as possible to promote multi-party information exchange and cognitive integration, making adjudication not only an authoritative conclusion but also a product of common semantic exploration.

Reconstruction of Desensitized Hearing Path and Prospect of "Semantic Hearing"

In this section, without involving specific identities, based on public information and semantic logic, we reconstruct and analyze the Hearing Procedure that may be carried out in the procuratorial protest stage of this case. Focus on restoring key DIKWP nodes in the hearing process, evaluating the impact of hearing as a semantic exchange mechanism on the adjudication path and its role in mediation, and exploring a system design of "Semantic Hearing" to strengthen communication at the semantic level in dispute resolution.

1. Brief Introduction to Hearing Background:

After losing the second instance, Party B (the losing party) was dissatisfied with the final judgment and applied to the procuratorial organ for legal supervision (i.e., civil procuratorial supervision procedure). After the Supreme People's Procuratorate accepted the case, in accordance with the requirements of judicial reform in recent years, it is possible that a Public Hearing was organized. The hearing invited third-party personnel (legal experts, deputies to the National People's Congress, members of the Chinese People's Political Consultative Conference, etc.) as hearing officers, as well as both parties to state their opinions. The purpose of the hearing is to promote the procuratorial organ to fairly review whether there is a wrong judgment in the case and whether a protest needs to be filed through public discussion. For this case, the focus of the hearing is still "how should the nature of the funds be identified", only this time hosted by a prosecutor instead of a judge, and the discussion focuses more on the supervision angle (whether the original judgment found facts clearly, applied law correctly, missed important evidence, etc.).

2. Key DIKWP Nodes in Hearing Process:

According to general hearing procedures, key nodes include: case introduction, party statement, hearing officer questioning and deliberation, and procuratorial organ decision stages. We reconstruct with DIKWP semantics as follows:

Node 1: Moderator (Prosecutor) Briefs Case and Focus of Dispute – Equivalent to providing Data Layer + Information Layer input for hearing officers. The moderator objectively states basic facts of the case (identities of both parties, contribution process, litigation results) as data, and then points out that the focus of the dispute lies in "both parties adhere to their own words on the nature of contribution, and the court adopted the lending view." This opening is actually a Semantic Calibration: focusing all participants on major divergences to avoid information fog. From DIKWP perspective, this is the prosecutor compressing the Knowledge/Wisdom of the court judgment into Information (focus issues) easy for hearing officers to understand and providing it to them. This step sets the tone for the hearing semantic path: clarifying the semantic coordinate axis of discussion (Lending vs Partnership).

Node 2: Applicant Statement (Party B) – B as the appellant speaks first, explaining reasons for dissatisfaction with the original judgment. Here B outputs the essence of his DIKWP path again: reiterating facts (Data), emphasizing semantics under his own perspective (Information: cooperative relationship), citing regulations and precedents favorable to himself (Knowledge) to argue the original judgment was wrong, and finally requesting the procuratorial organ to support retrial (Wisdom layer conclusion). B will also reveal his dissatisfaction and demands (Purpose layer). For example, B might state: "At that time, both parties agreed on profit sharing. I tried my best to operate, and company losses are also my losses. The court asked me to return principal and interest. I think this treats cooperation as lending, contrary to facts, hope the procuratorial organ corrects it." This statement session allows hearing officers to directly feel B's Semantic Tension Point: he thinks the court "Symbolic Adjudication" only looks at IOUs and ignores cooperation reality. For hearing officers, this is input from B system to their system's Data/Information layer, and they start to build cognition of B's view.

Node 3: Respondent Statement (Party A or Court Representative) – As a contrast, Party A (or the invited original trial court representative, if any) will state reasons supporting the original judgment, equivalent to outputting Lending Semantic Path again. A might say: "Our side emphasizes that there is no partnership agreement between the two parties, and I did not participate in operation. According to law, it should be recognized as lending. The original judgment maintained the principle of honesty and credibility. It is wrong for B to obtain funds in the name of cooperation but not want to pay back." Party A's speech reinforced another set of semantics. Hearing officers now acquired Two Parallel Information/Knowledge inputs, forming a contrast in mind. It is like hearing officers having two small DIKWP models of A and B running side by side in their brains. They might wonder: why are the statements of the two sides so different? At this moment, Hearing Officer DIKWP starts to operate actively, entering Information/Knowledge Processing stage.

Node 4: Hearing Officer Questioning and Discussion – This is the core interaction of the hearing. Hearing officers ask questions and express views based on statements just now. This process can be subdivided into several sub-nodes:

Questioning to Clarify Facts: Hearing officers may ask about facts not mentioned or vague by both parties, such as "Did you sign any written agreement or receipt at the beginning?" "After A provided funds, did he get fixed interest monthly?" etc. This is asking for missing information from both sides at Data Layer and Information Layer to complete the knowledge picture. For example, B has to admit there is no written agreement, A might have taken fixed income Vouchers, these new data will be included in consideration by hearing officers. Through questioning, hearing officers open up and share some data nodes of respective DIKWPs, reducing information asymmetry.

Questioning Logic of Both Parties: Hearing officers will also question both parties' arguments based on their own knowledge and experience. For example to B: "If you say it's partnership, why not make an agreement and not let the other party participate in management?" To A: "Since you say lending, why talk about dividends? Did you also want to earn more?" This questioning is hearing officers Stress Testing both parties' semantic paths at Knowledge Layer, seeing if there are self-contradictions or untenable points. On one hand, forcing out more detailed information, on the other hand also Testing Semantic Robustness. This is similar to judge questioning during court trial, only hearing officers come from multiple angles, questions might be sharper and more diverse.

Expert Explaining Law: If there are legal experts among hearing officers, they will express opinions on legal issues, belonging to Knowledge/Wisdom Layer Output. For example, an expert might say: "According to Supreme Court guidance, identifying partnership depends on whether there is agreement on shared losses. There is none in this case, so the original judgment makes sense." Another expert might think: "There are also cases where verbal partnership is recognized, should be viewed comprehensively." These professional insights provide High-level Knowledge for the hearing, guiding semantic evaluation standards. Hearing officers might discuss disputed points with each other, which is Wisdom Layer Confrontation: different opinions intertwine, finally seeking consensus.

Value and Reason Consideration: Hearing officers (especially NPC deputies, etc.) sometimes express views from fairness and reason. Such as "B contributed effort after all, it's unfair to judge repayment, can we mediate?" or "If everyone takes money and doesn't pay back like B, it will affect business environment." These remarks bring factors of Moral Purpose Layer into the semantic network, enriching discussion dimensions. This reminds prosecutors that both legal effects and social effects should be considered—if opinions lean towards B needing care, maybe it means the original judgment has certain bias.

In this process, the collective DIKWP system of hearing officers gradually forms its own judgment. They constantly incorporate A and B's answers into their Knowledge Layer, using Wisdom to judge who is more reasonable. Semantic Tension is fully released in the form of open debate at the hearing, and all parties can "speak their mind." This has positive significance for subsequent ruling: many dispute parties find it hard to accept judgment because they feel they haven't finished speaking or reasoning thoroughly. Hearing provides an opportunity to conquer hearts with semantics. When hearing officers start to lean towards one side, the other side is also easier to be convinced or psychologically accept.

Node 5: Prosecutor Summarizes Opinions and Announces Decision – After the hearing ends, the procuratorial organ makes a handling decision (protest or not) referring to the hearing situation. This link is equivalent to the final output of Procuratorial Organ DIKWP Wisdom Layer. If deciding to protest, it means the prosecutor adopted the majority opinion of the hearing believing the original judgment was wrong; if deciding not to protest, then believing the original judgment has no obvious problem. Either way, the prosecutor usually explains reasons on the spot or afterwards. This is similar to court judgment, only possibly informing verbally and concisely in form. For example: "After hearing opinions from all parties and experts, this procuratorate believes that the original judgment found facts clearly, evidence is insufficient to support the applicant's claim, and will not protest." Or conversely: "This procuratorate believes that the original judgment was improper in identifying legal relationships and will request the Supreme Court for retrial review." This summary transforms hearing discussion results into Formal Legal Semantics. Hearing officers' wisdom is reflected here through the prosecutor's decision. The prosecutor's intention (upholding justice, supervising error correction) is bound with the case handling outcome at this moment.

3. Assessment of Hearing Impact on Adjudication Path:

The actual result of this case is that the Supreme Procuratorate filed a protest, and the Supreme Court retrial still upheld the original judgment. Combined with hearing analysis, this reflects that the hearing has the following impacts on the adjudication path:

Broaden Information Sources, Increase Possibility of Correction: Hearing allows the case to undergo re-examination outside the court system. Expert hearing officers offer opinions from different angles, helping to discover points that the original trial might have ignored. If not for the hearing, some circumstances favorable to B might not have been valued. Hearing promoted protest, although eventually not changing the sentence, at least forced the Supreme Court to re-examine the case, making the adjudication more prudent and authoritative. It can be said that hearing added a "Semantic Loop" to the adjudication path, this extra round of semantic filtering greatly reduced the probability of wrongful cases.

Enrich Adjudication Reasons, Enhance Law Explanation and Reasoning: The Supreme Court will respond one by one to protest opinions in the retrial judgment. Since Party B and experts raised various arguments supporting cooperation at the hearing, the Supreme Court had to argue its rebuttal reasons in more detail in the judgment to convince the public. In fact, the Supreme Court judgment listed many reasons why B's claims were untenable, which might be responding one by one to problem points exposed during the hearing process. Thus, hearing objections forced adjudication reasoning to be fuller, making judgment semantics more persuasive.

Calm Parties' Mindset, Ease Contradictions: Although B did not win, the hearing process at least made him feel the smooth channel of appeal and respect for opinions being heard. Procuratorial organs supporting protest also to some extent recognized part of B's claims (i.e., the case has value for re-examination). After the Supreme Court's final ruling, although disappointed, B experienced an open and fair discussion process, and resistance to the judgment might decrease. From reality, if the losing party still cannot convince others after procuratorial hearing, most will choose to give up or turn to rational handling. Party A also further confirmed its own legitimacy through the hearing, thus becoming firmer. Overall, hearing provided a platform for conflicting parties to vent and communicate, Emotional Tension was released in time, avoiding intensification into extreme confrontation.

Guide Trial Direction of Similar Cases: Hearing records are often publicly reported or internally circulated, and experts' views and protest opinions may play a guiding role in future trials of similar cases. If experts supported cooperation determination in this case hearing but were still denied by the court, then the signal to judges nationwide is: Unless there is clear evidence, lend when risk-sharing elements are insufficient. The publicity of such case discussions helps unify judicial standards. In the long run, hearing feedback may even promote legal improvement (e.g., aimed at this "cooperation in name, lending in reality" situation, the Supreme Court Civil Division later issued typical cases or reply guidance). So the impact of hearing on adjudication semantic path is not only reflected in individual cases but more likely to affect institutional levels through semantic propagation.

4. Discussion on "Semantic Hearing" System Design:

Combined with the above analysis, we propose the concept of "Semantic Hearing", aimed at strengthening the application of hearing procedures in justice to achieve semantic consistency trial:

Early Intervention Mechanism: Move hearings forward, introducing hearings in major difficult cases in the first or second instance. Courts actively invite third parties to witness discussions, enabling full semantic confrontation of disputes before judgment. This is similar to jury consultation or expert argumentation systems. Through early hearings, the court has digested different semantic opinions when making a ruling, which can reduce appeals and complaints.

Full Semantic Recording and Analysis: Hearings should be recorded and videotaped throughout, and semantic analysis technology used to establish Semantic Logs: recording key concepts and viewpoint changes used by all parties. This not only serves on-spot discussion but also provides materials for judges to organize thoughts afterwards. AI can annotate emotions and dispute points on semantic logs, prompting judges which points have the most divergence and need to be explained clearly in the judgment.

Incorporating Hearing Opinions into Judgment: Drawing on the jury system, main opinions of all parties at the hearing and reasons for court adoption or rejection can be written in the judgment. In this way, parties can clearly see that their views have been considered, knowing reasons even if rejected. This achieves Adjudication Semantic Dialogue, reducing authoritative stiffness, making it easier for the losing party to accept.

Multi-subject Participation: Semantic hearings should not be limited to legal experts but can add representatives from various fields according to case types, ensuring discussion covers professional knowledge and social common sense. For example, involving investment and financing disputes, senior investors can be invited to express views, making up for judges' lack of commercial experience, making adjudication semantics closer to industry semantics, not mechanical.

Combination of Hearing and Mediation: During the hearing, mediation possibilities should be explored simultaneously. If hearing officers unanimously agree on settlement, negotiation of parties should be promoted. Hearing officers can even propose Semantic Compromise Plans: such as "A returns principal and interest halved, both parties no longer entangled," such suggestions proposed by third parties are often easier to accept. If parties agree, disputes are resolved before judgment, achieving true win-win. Even if not agreeing, it lays the groundwork for later enforcement settlement (e.g., after judgment takes effect, parties may refer to hearing suggestions to make partial concessions to reach enforcement settlement).

Open and Transparent Principle: Unless confidential, hearings should be conducted publicly to enhance judicial transparency. This conveys to the public the openness of justice seeking diverse opinions, and also makes judgment results easier to obtain public support. When society sees that a case has undergone full discussion but still made a certain ruling, doubts will decrease. This is especially important for those judgments that seem unkind in language but reasonable in semantics. For example, judging lending in this case, superficially A gets money back and B loses money seems harsh, but public discussion reveals B indeed took risks without evidence, then the public also understands the necessity of judgment, thereby supporting judicial authority.

Through the "Semantic Hearing" system, we look forward to the judicial process truly moving from Adversarial to Consultative, from pure legal provision application to Semantic Fusion. It improves the deficiencies of traditional court trials: in court, judges look down from above, parties are sometimes cautious and defensive, not necessarily expressing true thoughts fully; while hearing atmosphere is relatively relaxed, parties are more willing to speak freely, and semantic exchange is smoother. In addition, hearing introduces external perspectives, which can correct professional bias and avoid "court's one-sided word." Ultimately, adjudication conclusions will be built on a more solid semantic consensus basis, reducing resistance and misunderstanding.

Conclusion and Institutional Suggestions

Through in-depth semantic analysis of this case, we draw several inspirations and propose suggestions for optimizing judicial adjudication processes accordingly, aiming to promote judicial practice from "Linguistic Symbol Adjudication" to "Semantic Consistency Trial", recognizing parties' contributions at all levels more fairly.

1. Summary of Adjudication from Semantic Perspective:

The XXX case (after desensitization) is essentially a dispute caused by Semantic Dislocation. Parties A and B had different connotative expectations for the word "cooperation," leading to falling into the controversial cliché of "investment or lending" legally. The court finally stripped away linguistic appearances and restored the Semantic Essence of the transaction (lending relationship) based on objective evidence and legal standards. This ruling maintained legal certainty but also reminds people: Use of legal language must be clear and consistent, otherwise semantic deviation will trigger rights conflicts. The DIKWP model helped us dissect the multi-layer semantics of the case and found that the key to resolving disputes lies in Precise Identification and Alignment of Semantics. Justice is not simply looking at what both parties wrote on the contract, but exploring their True Data Facts, Information Understanding, Knowledge Background, and Intention Purpose, and then making wisdom judgments. This practice ensures adjudication results conform to the same semantic standard, rather than sticking to one party's wording or expression. Therefore, introducing DIKWP semantic analysis into justice helps improve substantial justice and interpretability of adjudication.

2. Establish Semantic Consistency Trial Mechanism:

To reduce disputes caused by language understanding differences, justice should advocate Semantic Consistency principle, specifically improving from the following aspects:

Intervention in Contract Review Stage: When concluding transactions, intervene through notarization, legal advisors, etc., to help parties Clarify Semantics. For example, concretize ambiguous words like "cooperation" and "investment," adding clauses like "if risk bearing is not agreed, it is regarded as lending." This is equivalent to pre-aligning Information and Knowledge layers of both parties in DIKWP model, avoiding future disputes.

Strengthen Right of Clarification in Litigation: Judges should make good use of the right of clarification in court, asking questions in time about unclear semantics or implied assumptions in both parties' views, requiring clarification. For example, in this case, the judge can directly ask A: "Does the cooperation in your mouth refer to fixed income?" Ask B: "Do you think cooperation includes returning principal?" Through court Q&A, spread out respective intentions to talk, reducing semantic minefields. This clarification of key concepts is equivalent to realizing a semantic hearing during trial, enabling the judge to figure out the words behind words, so that adjudication can be grounded. This requires judges to have stronger language understanding and communication skills, and also requires institutional guarantee for sufficient clarification without overstepping.

Strengthen Semantic Reasoning in Judgment Documents: Judgments should explain core language concepts used by parties, Translating into Legal Semantics. As the judgment of this case actually already did so: pointing out "although called cooperation, without shared risk agreement, legally does not constitute partnership." In the future, courts should use more of this "first quote party's words, then explain its legal meaning" reasoning mode to help parties and the public understand the judgment. This helps bridge the gap between legal language and public language, making adjudication results easier to understand and accept.

Introduce Semantic Analysis Auxiliary Tools: Develop judicial semantic analysis systems, perform NLP (Natural Language Processing) on party statements and evidence texts, extract key entities and relationships therein, and contrast with legal knowledge graphs, prompting judges of possible semantic deviations. For example, the system finds a contract called "Cooperation Agreement" but clauses are all fixed returns without loss clauses, automatically reminding "suspected lending disguise." This tool is like a semantic radar, detecting inconsistencies between language and legal standards in advance for judge's reference. This will greatly improve efficiency and avoid human oversight.

3. Incorporate Non-traditional Contribution Recognition Mechanism:

Aiming at the problem that current law pays insufficient attention to soft contributions like wisdom, we suggest establishing Non-traditional Capital Contribution Recognition System in civil adjudication:

Legislative Level: Modify or improve relevant laws. Such as clarifying in "Civil Code · Contract Part" or separate regulations: "Labor, knowledge, skills, etc. paid by parties for common purposes can be converted into capital contribution, enjoying corresponding rights compared to monetary contribution." Or adding clauses: "When liquidating partnership, labor contribution of each partner should be considered. For those who obviously invested more labor but received no income, appropriate compensation can be given when distributing remaining assets." These clauses make wisdom contribution explicit.

Judicial Interpretation Level: The Supreme Court can issue interpretations listing how to identify labor contribution, intellectual property contribution, and how to handle in partnership/joint venture disputes. Such as stipulating "For those contributing shares with technology or management experience valuation, treat as shares according to agreement; if no agreement, the court decides profit distribution at discretion based on contribution size and project benefit." For cases like this one with no clear agreement but labor contribution, it can also guide: "If the funder demands return of investment funds without result while the other party obtains actual benefits, partial support can be given by measuring labor value with unjust enrichment or principle of fairness." This will endow judges with basis for discretion according to law.

Trial Practice Level: Judges should actively guide parties to provide proof of respective soft contributions during case trial, and state in the judgment that these factors were considered. Even if final characterization is unfavorable to one party, recognition of their diligent effort can be expressed in the judgment, thereby making some care in results (such as extending grace period, installment repayment, etc.). This warm consideration reflects the humanistic care of justice, making law not appear cold.

Evaluation System Level: Introducing professional assessment is necessary for identifying wisdom contribution. Judicial intellectual asset assessment agencies can be established, similar to appraisers, making value analysis reports on contributions of all parties in disputes, providing reference for courts. Accountants and appraisers should play a role in this aspect. For example, let them assess the market value of operation management in a startup project, thereby inferring B's labor "deserved remuneration." The court can balance interests in judgment based on this. This third-party evaluation is also conducive to parties being more convinced of the ruling because numbers are objectively calculated.

4. AI-assisted Trial Model Construction:

The DIKWP model itself originates from the field of artificial intelligence. We suggest combining the judicial system with AI to develop cognitive reasoning models like "DIKWP-GPT" to assist judges in handling cases. This model can perform five-layer semantic processing on input case facts:

Data Layer extracts fact points;

Information Layer gives possible interpretations of all parties;

Knowledge Layer retrieves relevant legal regulations and cases;

Wisdom Layer outputs several adjudication schemes based on different settings (such as different results leaning towards protecting investors or protecting operators);

Purpose Layer evaluates the value goals and potential impacts achieved by each scheme.

Judges can converse with the model, for example asking: "What about law and reason if judged as lending? What about judging as partnership?" The model will call out semantic links supporting each scheme from its knowledge base (e.g., citing existing precedents). In this way, judges obtain panoramic reference before decision-making, avoiding ill-considered thoughts. AI can also be used for Tension Broken Link Detection (mentioned before), checking judgment logic loopholes, or for Language Wording Optimization, making judgment wording approachable yet accurate. Through AI simulating multi-agent cognitive collision (such as simulating hearing discussion), judges can foresee reactions of parties and public to judgment, thereby adjusting reasoning and results. This will truly land the DIKWP model in trial practice, making trials smarter and more transparent.

5. Improve Semantic Literacy of Judicial Personnel:

Finally, institutional improvement ultimately falls on people. It is necessary to strengthen training of judges and prosecutors in semantic analysis and communication. Legal professionals traditionally focus on legal provisions and logic, but this case inspires us Must also be experts in language and psychology. Suggest adding cognitive linguistics, negotiation skills, psychology, etc. to judicial training courses, enabling case handlers to keenly capture meanings behind words, know how to listen, and be good "interpreters" and "mediators" in dialogue. When judicial personnel themselves possess semantic sensitivity, they can naturally actively use means like hearing and clarification in procedures to ensure semantic consistency.

In summary, through desensitized reconstruction and DIKWP semantic analysis of typical cases, this report demonstrates that the controversial essence of "Cooperation vs. Investment" disputes lies in Inconsistency of Multi-layer Semantics. We propose that justice should comply with requirements of the intelligent era, upgrading from rule adjudication to Semantic Adjudication: not only strictly following legal logic but also being good at analyzing and bridging semantic gaps of all parties, recognizing all-round contributions of parties. By introducing diverse mechanisms like hearings and AI tools, courts can enhance Humanity and Flexibility while maintaining adjudication Predictability. When the adjudication process achieves semantic alignment, and when judgment results reflect the balance of values at all layers, judicial credibility and social satisfaction will rise accordingly. This is both the humanistic pursuit of judicial reform and an important development direction for future AI-assisted trial models. We believe that with the integrated application of new theories like DIKWP cognitive model, judicial adjudication will gradually bid farewell to the stereotype of seeing only language but not human hearts, stepping into a new realm of Semantic Consistency and Substantive Justice.

References

Understand in one article: Partnership, Investment, or Lending? How to Distinguish and Identify, https://morunlaw.com/sys-nd/243.html

DIKW pyramid - Wikipedia, The Free Encyclopedia, https://en.wikipedia.org/wiki/DIKW_pyramid

(PDF) Overview of Professor Yucong Duan's DIKWP Model and Related Theories, https://www.researchgate.net/publication/396555838_duanyucongjiaoshouDIKWPmoxingjixiangguanlilunzongshu

Case Explanation: How to Assess Value and Operate Technology Shares? - Zhihu, https://zhuanlan.zhihu.com/p/610104561

Exploration of Issues Related to Non-monetary Capital Contribution by Shareholders of Limited Liability Companies under the Background of New "Company Law", https://www.everbrightlaw.com/CN/07/eae9935a396c1878.aspx

Research on the Core Role of DIKWP Model in Human-Machine Bidirectional Cognitive Language - Yucong Duan's Blog - Blog, http://https--blog--sciencenet--cn.proxy.xianning.gov.cn/blog-3429562-1479817.html

Large Language Model Consciousness Level "Cognitive Quotient" White-box DIKWP Evaluation 2025 Report Released - Science and Technology Daily, https://www.std

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