Triple
T25039459
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Eusko Legebiltzarra |
E627068
|
entity |
| Predicate | seatsPerProvince |
P76381
|
FINISHED |
| Object | 25 |
—
|
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: 25 | Statement: [Eusko Legebiltzarra, seatsPerProvince, 25]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: seatsPerProvince Context triple: [Eusko Legebiltzarra, seatsPerProvince, 25]
-
A.
regionSeatsCount
chosen
Indicates the number of seats allocated or available within a specific region.
-
B.
hasEqualSeatAllocationPerProvince
Indicates that each province is assigned the same number of seats in a given allocation or representation system.
-
C.
seatsPerRow
Indicates the number of seats that are arranged in each row within a seating layout or configuration.
-
D.
individualSeats
Indicates that an entity provides or consists of separate, single-person seating positions rather than shared or bench-style seating.
-
E.
populationProvince
Indicates that a specified population figure is associated with, or belongs to, a particular province.
- 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_69e2ff2a2c088190be513727ee8bfe78 |
completed | April 18, 2026, 3:48 a.m. |
| NER | Named-entity recognition | batch_69f45309e63c8190bd2a221a6cd03077 |
completed | May 1, 2026, 7:15 a.m. |
| PD | Predicate disambiguation | batch_69f442c861188190967655c6d8012380 |
completed | May 1, 2026, 6:06 a.m. |
Created at: April 18, 2026, 6:08 a.m.