Triple
T22491693
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Union of the Democratic Centre (Spain) |
E556032
|
entity |
| Predicate | numberOfSeatsWonIn1977Congress |
P31127
|
FINISHED |
| Object | 166 |
—
|
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: 166 | Statement: [Union of the Democratic Centre (Spain), numberOfSeatsWonIn1977Congress, 166]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfSeatsWonIn1977Congress Context triple: [Union of the Democratic Centre (Spain), numberOfSeatsWonIn1977Congress, 166]
-
A.
speakerSeatsWon
Indicates the number of seats won by the entity serving or designated as the speaker in a given election or legislative context.
-
B.
ppcSeatsWon
Indicates the number of seats that the PPC has won in an election or legislative body.
-
C.
numberOfSeatsWon
chosen
Indicates the quantity of seats secured by an entity (such as a party or candidate) in an election or representative body.
-
D.
representedInCongressBy
Indicates that one entity serves as the official congressional representative (e.g., legislator) for another entity (such as a person, group, or geographic area).
-
E.
wonMostChamberOfDeputiesSeats
Indicates that an entity secured the highest number of seats in the Chamber of Deputies in a given election or time period.
- 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_69e11e5445bc8190b6a9481926db3355 |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f15caea9d081909adc90ae78999d53 |
completed | April 29, 2026, 1:19 a.m. |
| PD | Predicate disambiguation | batch_69e898be31448190be5ae7f5656f0497 |
completed | April 22, 2026, 9:45 a.m. |
Created at: April 16, 2026, 8:49 p.m.