Triple
T18045360
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Israeli legislative election, 1973 |
E431756
|
entity |
| Predicate | seatCount_CenterList |
P129606
|
FINISHED |
| Object | 3 |
—
|
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: 3 | Statement: [Israeli legislative election, 1973, seatCount_CenterList, 3]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: seatCount_CenterList Context triple: [Israeli legislative election, 1973, seatCount_CenterList, 3]
-
A.
regionSeatsCount
Indicates the number of seats allocated or available within a specific region.
-
B.
seatCount
Indicates the number of seats associated with an entity, such as a venue, vehicle, or room.
-
C.
individualSeats
Indicates that an entity provides or consists of separate, single-person seating positions rather than shared or bench-style seating.
-
D.
hasNumberOfCentres
Indicates the relationship specifying how many centers (or central units/locations) are associated with a given entity.
-
E.
seatLocatedAt
Indicates that a seat is positioned or situated at a specific location or place.
- 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_69d8b906482481908183315b9ecf9994 |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e4bff202088190ae971879348e2294 |
completed | April 19, 2026, 11:43 a.m. |
| PD | Predicate disambiguation | batch_69e3f908da508190a088aa837ea5b7af |
completed | April 18, 2026, 9:35 p.m. |
| PDg | Predicate description generation | batch_69e42d8eefa88190a700c7c1b4213e46 |
completed | April 19, 2026, 1:19 a.m. |
Created at: April 10, 2026, 10:25 a.m.