Triple
T18150485
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Israeli legislative election, 1981 |
E434486
|
entity |
| Predicate | wasCloselyContested |
P28795
|
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: [Israeli legislative election, 1981, wasCloselyContested, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: wasCloselyContested Context triple: [Israeli legislative election, 1981, wasCloselyContested, true]
-
A.
wasCloseElection
chosen
Indicates that an election was decided by a very small margin between candidates or options.
-
B.
wasContestedBetween
Indicates that an event, position, or resource was the subject of competition or dispute involving two or more opposing parties.
-
C.
wasContestedIn
Indicates that an event, position, or decision was the subject of competition, dispute, or challenge within a particular context or proceeding.
-
D.
hasOfficeContested
Indicates that an individual has been a candidate for a particular public office in an election.
-
E.
alsoContestedIn
Indicates that the same issue, claim, or matter is being disputed or challenged in another context, case, or proceeding as well.
- 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_69d8b90aac308190801e2c57d8c5bfe5 |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e4de3812e8819097f025476d5c6a1d |
completed | April 19, 2026, 1:52 p.m. |
| PD | Predicate disambiguation | batch_69e43317d11c81908d1dc14921566b47 |
completed | April 19, 2026, 1:42 a.m. |
Created at: April 10, 2026, 10:29 a.m.