Triple
T27035109
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Keret epic |
E681029
|
entity |
| Predicate | hasFragmentaryEnding |
P42590
|
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: [Keret epic, hasFragmentaryEnding, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasFragmentaryEnding Context triple: [Keret epic, hasFragmentaryEnding, true]
-
A.
hasUnfinishedEnding
chosen
Indicates that an entity concludes in an incomplete, unresolved, or open-ended manner rather than reaching a fully finished state.
-
B.
hasAmbiguousEnding
Indicates that the event, story, or situation concludes in a way that is open to multiple interpretations or lacks a clear, definitive resolution.
-
C.
hasEnding
Indicates that one entity concludes with, or terminates in, another entity (such as a specific substring, segment, or final component).
-
D.
hasConditionalEnding
Indicates that one entity concludes or terminates only if a specified condition involving another entity is met.
-
E.
hasFinalSyllable
Indicates that one entity possesses or ends with a specific final syllable represented by the other entity.
- 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_69eeeb5566f08190813daf896fa3da04 |
completed | April 27, 2026, 4:51 a.m. |
| NER | Named-entity recognition | batch_69f657f653448190a945b4751af8507d |
completed | May 2, 2026, 8 p.m. |
| PD | Predicate disambiguation | batch_69f6575ba12081909396036f78757a76 |
completed | May 2, 2026, 7:58 p.m. |
Created at: April 27, 2026, 7:15 a.m.