Triple

T20558666
Position Surface form Disambiguated ID Type / Status
Subject Kripke–Kleene semantics in logic programming E504786 entity
Predicate relatedTo P37 FINISHED
Object well-founded semantics
Well-founded semantics is a three-valued semantics for logic programs that assigns a unique, typically partial model to handle recursion and negation in a principled way.
 E504786 NE FINISHED

How this triple was built (4 steps)

Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.

NER Named-entity recognition gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: well-founded semantics | Statement: [Kripke–Kleene semantics in logic programming, relatedTo, well-founded semantics]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: well-founded semantics
Context triple: [Kripke–Kleene semantics in logic programming, relatedTo, well-founded semantics]
  • A. Herbrand semantics
    Herbrand semantics is a formal framework in logic and automated theorem proving that interprets first-order formulas over the Herbrand universe of ground terms to define truth and satisfiability.
  • B. Kripke–Kleene semantics in logic programming
    Kripke–Kleene semantics in logic programming is a three-valued, fixed-point-based approach to interpreting logic programs that captures partial or undefined information without committing to classical true/false evaluations.
  • C. Kripke semantics
    Kripke semantics is a framework in modal and non-classical logic that interprets formulas via possible worlds and accessibility relations to model notions like necessity, possibility, and intuitionistic truth.
  • D. Stalnaker semantics
    Stalnaker semantics is a possible-worlds framework for understanding conditionals, where the truth of a conditional depends on what is true in the closest possible world where its antecedent holds.
  • E. Fitting semantics for modal logic
    Fitting semantics for modal logic is a framework in mathematical logic that extends Kripke-style semantics to provide a more general and often intuitionistic treatment of modal operators.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: well-founded semantics
Triple: [Kripke–Kleene semantics in logic programming, relatedTo, well-founded semantics]
Generated description
Well-founded semantics is a three-valued semantics for logic programs that assigns a unique, typically partial model to handle recursion and negation in a principled way.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: well-founded semantics
Target entity description: Well-founded semantics is a three-valued semantics for logic programs that assigns a unique, typically partial model to handle recursion and negation in a principled way.
  • A. Herbrand semantics
    Herbrand semantics is a formal framework in logic and automated theorem proving that interprets first-order formulas over the Herbrand universe of ground terms to define truth and satisfiability.
  • B. Kripke–Kleene semantics in logic programming chosen
    Kripke–Kleene semantics in logic programming is a three-valued, fixed-point-based approach to interpreting logic programs that captures partial or undefined information without committing to classical true/false evaluations.
  • C. Kripke semantics
    Kripke semantics is a framework in modal and non-classical logic that interprets formulas via possible worlds and accessibility relations to model notions like necessity, possibility, and intuitionistic truth.
  • D. Stalnaker semantics
    Stalnaker semantics is a possible-worlds framework for understanding conditionals, where the truth of a conditional depends on what is true in the closest possible world where its antecedent holds.
  • E. Fitting semantics for modal logic
    Fitting semantics for modal logic is a framework in mathematical logic that extends Kripke-style semantics to provide a more general and often intuitionistic treatment of modal operators.
  • F. None of above.

Provenance (5 batches)

The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.

Step Stage Batch ID Status When
creating Elicitation batch_69e0b4b6587c8190aee63dc7cff244ea completed April 16, 2026, 10:06 a.m.
NER Named-entity recognition batch_69e6a5e178648190910795bae5422e50 completed April 20, 2026, 10:17 p.m.
NED1 Entity disambiguation (via context triple) batch_6a08a5796df48190b96841c94a6311c0 completed May 16, 2026, 5:12 p.m.
NEDg Description generation batch_6a08a68c08dc8190a09854800df82686 completed May 16, 2026, 5:17 p.m.
NED2 Entity disambiguation (via description) batch_6a08a7331cc88190a9ed6056e5743e69 completed May 16, 2026, 5:19 p.m.
Created at: April 16, 2026, 11:38 a.m.