Triple
T3390237
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kripke fixed-point theory of truth |
E71398
|
entity |
| Predicate | allowsTruthValue |
P273
|
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 fixed-point theory of truth, allowsTruthValue, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: allowsTruthValue Context triple: [Kripke fixed-point theory of truth, allowsTruthValue, true]
-
A.
numberOfTruths
Indicates the quantity of statements or propositions that are true within a given context or set.
-
B.
isValuedFor
Indicates that one entity is appreciated, esteemed, or considered important because of a particular quality, contribution, or characteristic it provides to another entity.
-
C.
allowedReturn
Indicates that an entity is permitted to be returned or sent back under specified conditions or rules.
-
D.
supportsValue
Indicates that one entity provides justification, evidence, or backing for the truth, relevance, or appropriateness of a particular value associated with another entity.
-
E.
allows
chosen
Indicates that one entity grants permission, capability, or opportunity for another entity to perform an action or be in a certain state.
- 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_69ad85a9c4a88190a854019341cb3b60 |
completed | March 8, 2026, 2:20 p.m. |
| NER | Named-entity recognition | batch_69adb6682c708190b76a7a16cee7c5aa |
completed | March 8, 2026, 5:48 p.m. |
| PD | Predicate disambiguation | batch_69adadf705608190975423779430cc58 |
completed | March 8, 2026, 5:12 p.m. |
Created at: March 8, 2026, 3:14 p.m.