Triple
T28195031
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | FEL-1 |
E716419
|
entity |
| Predicate | coherence |
P146190
|
FINISHED |
| Object | coherent |
—
|
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: coherent | Statement: [FEL-1, coherence, coherent]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: coherence Context triple: [FEL-1, coherence, coherent]
-
A.
typeOfCoherence
Indicates the specific kind or category of coherence that characterizes the relationship between the related elements.
-
B.
isCoherent
chosen
Indicates that the elements of something are logically consistent, well-organized, and fit together in a unified, intelligible way.
-
C.
coerces
Indicates that one entity forces or pressures another entity to act against their will or better judgment.
-
D.
cooperativePrinciple
Indicates that one party is acting in accordance with shared conversational norms or mutual goals to facilitate effective, collaborative interaction with another party.
-
E.
arity
Indicates the number of arguments or participants that a relation or function takes.
- 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_69efd6b612f48190a72012b520afbd10 |
completed | April 27, 2026, 9:35 p.m. |
| NER | Named-entity recognition | batch_69f642d058188190b71796a530a202f6 |
completed | May 2, 2026, 6:30 p.m. |
| PD | Predicate disambiguation | batch_69f63c6c1a948190b68c0f92c264cc0c |
completed | May 2, 2026, 6:03 p.m. |
Created at: April 27, 2026, 10:27 p.m.