Triple
T16893637
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Israeli legislative election, 1961 |
E424238
|
entity |
| Predicate | seatCountOfProgressAndDevelopment |
P124900
|
FINISHED |
| Object | 1 |
—
|
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: 1 | Statement: [Israeli legislative election, 1961, seatCountOfProgressAndDevelopment, 1]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: seatCountOfProgressAndDevelopment Context triple: [Israeli legislative election, 1961, seatCountOfProgressAndDevelopment, 1]
-
A.
seatCount
Indicates the number of seats associated with an entity, such as a venue, vehicle, or room.
-
B.
definesNumberOfSeats
Indicates that an entity specifies or determines the total number of seats associated with another entity.
-
C.
hasGeneralSeats
Indicates that an entity possesses or includes general (non-reserved) seats in a seating or allocation context.
-
D.
seatingCapacity
Indicates the maximum number of people that something (typically a venue or vehicle) is designed or allowed to seat.
-
E.
previousNumberOfSeats
Indicates the number of seats an entity had before a change or update in its seating count.
- 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_69d889da3e8c8190a2b118f383f0beac |
completed | April 10, 2026, 5:25 a.m. |
| NER | Named-entity recognition | batch_69e3bbc6b97c8190b18aca477d6ef647 |
completed | April 18, 2026, 5:13 p.m. |
| PD | Predicate disambiguation | batch_69e32b90ec3c819099c51bb7baf2984c |
completed | April 18, 2026, 6:58 a.m. |
| PDg | Predicate description generation | batch_69e32e2c07b081908c8fee9f5507bb9e |
completed | April 18, 2026, 7:09 a.m. |
Created at: April 10, 2026, 5:29 a.m.