Triple
T34017673
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 2017 Catalan regional election |
E872290
|
entity |
| Predicate | wonPluralityOfSeats |
P122215
|
FINISHED |
| Object | Together for Catalonia |
—
|
NE NERFINISHED |
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: Together for Catalonia | Statement: [2017 Catalan regional election, wonPluralityOfSeats, Together for Catalonia]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: wonPluralityOfSeats Context triple: [2017 Catalan regional election, wonPluralityOfSeats, Together for Catalonia]
-
A.
majoritySeats
Indicates that one party or group holds more than half of the available seats in a governing or decision-making body.
-
B.
numberOfSeatsWon
Indicates the quantity of seats secured by an entity (such as a party or candidate) in an election or representative body.
-
C.
partyWinningMostSeats
chosen
Indicates which political party has secured the highest number of seats in an election or legislative body.
-
D.
citizensSeatsWon
Indicates the number of legislative or representative seats won by citizens (or citizen-backed entities) in an election or governing body.
-
E.
wonParliamentaryElection
Indicates that one party or candidate achieved victory in a parliamentary election over others.
- 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_69f349a19ad88190ab586f010c804a8f |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_69f70fb4f18c819099ef6d9177b7d205 |
completed | May 3, 2026, 9:04 a.m. |
| PD | Predicate disambiguation | batch_69f70f3a54d481909ba6bdda3647b761 |
completed | May 3, 2026, 9:02 a.m. |
Created at: May 1, 2026, 1:51 a.m.