Triple
T29585745
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 1987 Fijian coups d'état |
E754014
|
entity |
| Predicate | numberOfCoups |
P201591
|
FINISHED |
| Object | 2 |
—
|
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: 2 | Statement: [1987 Fijian coups d'état, numberOfCoups, 2]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfCoups Context triple: [1987 Fijian coups d'état, numberOfCoups, 2]
-
A.
nombreDeParties
Indicates the number of parts or segments associated with an entity in the relationship.
-
B.
numberOfTurns
Indicates the total count of discrete turns or rotations involved in an interaction, process, or motion.
-
C.
numberOfDraws
Indicates the total count of times an event, game, or contest has ended in a draw or tie.
-
D.
numberOfMovements
Indicates the total count of distinct movements or motion events associated with the given entity or context.
-
E.
numberOfKnownPlays
Indicates the total count of plays that are known to be associated with a given entity (such as an author, theater, or period).
- F. None of above. chosen
Provenance (4 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_69f0ef836ac88190bd809dc58b5ec907 |
completed | April 28, 2026, 5:33 p.m. |
| NER | Named-entity recognition | batch_6a000a1d8fa88190a1d82ac746565c48 |
completed | May 10, 2026, 4:31 a.m. |
| PD | Predicate disambiguation | batch_6a0008b26eb88190ae03b2309a614774 |
completed | May 10, 2026, 4:25 a.m. |
| PDg | Predicate description generation | batch_6a000a1c8f8881908293ab4f7207d25f |
completed | May 10, 2026, 4:31 a.m. |
Created at: April 28, 2026, 6:10 p.m.