Triple
T20558656
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kripke–Kleene semantics in logic programming |
E504786
|
entity |
| Predicate | usesTruthValues |
P92650
|
FINISHED |
| Object | true |
—
|
LITERAL FINISHED |
How this triple was built (2 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: true | Statement: [Kripke–Kleene semantics in logic programming, usesTruthValues, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usesTruthValues Context triple: [Kripke–Kleene semantics in logic programming, usesTruthValues, true]
-
A.
numberOfTruths
Indicates the quantity of statements or propositions that are true within a given context or set.
-
B.
associatesTruthValuesWith
chosen
Indicates a relationship that links entities to the truth values assigned to them (such as true, false, or other logical values).
-
C.
isValuedFor
Indicates that one entity is appreciated, esteemed, or considered important because of a particular quality, contribution, or characteristic it provides to another entity.
-
D.
evaluatesAs
Indicates that one entity is judged, interpreted, or assessed as having a particular value, role, or classification in relation to another.
-
E.
logicalPolarity
Indicates that the truth value of a statement is affirmed (positive) or denied (negative) relative to some logical context.
- F. None of above.
Provenance (3 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. |
| PD | Predicate disambiguation | batch_69e59ff0116c8190a163ff28ed01430a |
completed | April 20, 2026, 3:39 a.m. |
Created at: April 16, 2026, 11:38 a.m.