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 |
—
|
NE NERFINISHED |
How this triple was built (3 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.
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 (2 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. |
Created at: April 16, 2026, 11:38 a.m.