Triple
T18307953
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Israeli legislative election, 1984 |
E438537
|
entity |
| Predicate | alignmentSeatsWon |
P131275
|
FINISHED |
| Object | 44 |
—
|
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: 44 | Statement: [Israeli legislative election, 1984, alignmentSeatsWon, 44]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: alignmentSeatsWon Context triple: [Israeli legislative election, 1984, alignmentSeatsWon, 44]
-
A.
seatWinner
Indicates that a particular candidate or party has won a specific seat (e.g., in an election or contest).
-
B.
seatsAreAllocatedTo
Indicates that specific seats are assigned or designated to particular entities (such as people, groups, or bookings).
-
C.
individualSeats
Indicates that an entity provides or consists of separate, single-person seating positions rather than shared or bench-style seating.
-
D.
seatsAllocatedBy
Indicates that seats are assigned or distributed by a particular agent, authority, or mechanism.
-
E.
seatAllocationLevel
Indicates the degree or priority level at which seats are assigned or distributed among eligible entities.
- 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_69d8b915e3e881909125d760c15d0c29 |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e50215e0c48190a4679d432b6ee596 |
completed | April 19, 2026, 4:25 p.m. |
| PD | Predicate disambiguation | batch_69e44fdf43d08190bbcfb6b1fe3cc0ee |
completed | April 19, 2026, 3:45 a.m. |
| PDg | Predicate description generation | batch_69e451a0ba208190a5fe92832a8f7a49 |
completed | April 19, 2026, 3:53 a.m. |
Created at: April 10, 2026, 10:35 a.m.