Triple
T5771757
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | November 2019 Spanish general election |
E127345
|
entity |
| Predicate | PSOESeats |
P31127
|
FINISHED |
| Object | 120 |
—
|
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: 120 | Statement: [November 2019 Spanish general election, PSOESeats, 120]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: PSOESeats Context triple: [November 2019 Spanish general election, PSOESeats, 120]
-
A.
UnidasPodemosVoteSharePercentage
Indicates the percentage of total votes received by Unidas Podemos in an election.
-
B.
thirdLargestPartyBySeats
Indicates that the subject is the political party holding the third-highest number of seats in a specified legislative body or election context.
-
C.
seatsWonBySDPLiberalAlliance
Indicates the number of legislative or electoral seats that were won by the SDP–Liberal Alliance in a given election or contest.
-
D.
numberOfSeatsWon
chosen
Indicates the quantity of seats secured by an entity (such as a party or candidate) in an election or representative body.
-
E.
proportionalRepresentationSeats
Indicates that the number of seats allocated to an entity is determined according to a proportional representation system based on its share of votes or support.
- 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_69c00834f6308190851b0abeddd8ed7e |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c02acb12c081908e4beee4a957f9f9 |
completed | March 22, 2026, 5:45 p.m. |
| PD | Predicate disambiguation | batch_69c021ce8d3c81909b332cb1c33a61ad |
completed | March 22, 2026, 5:07 p.m. |
Created at: March 22, 2026, 3:50 p.m.