Triple
T22607008
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Teruel Existe |
E566586
|
entity |
| Predicate | numberOfDeputiesWonIn2019 |
P7693
|
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: [Teruel Existe, numberOfDeputiesWonIn2019, 1]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfDeputiesWonIn2019 Context triple: [Teruel Existe, numberOfDeputiesWonIn2019, 1]
-
A.
seatsWonIn2019ParliamentaryElection
Indicates the number of seats an entity secured in the 2019 parliamentary election.
-
B.
numberOfMEPsWonIn2019EuropeanElection
Indicates the number of Members of the European Parliament that an entity secured in the 2019 European Parliament election.
-
C.
numberOfSeatsWonIn2019ParliamentaryElection
chosen
Indicates the number of seats an entity won in the 2019 parliamentary election.
-
D.
electionResult2019
Indicates the outcome or status of an entity in the 2019 election, such as who won, lost, or what result was obtained.
-
E.
numberOfSeatsWon
Indicates the quantity of seats secured by an entity (such as a party or candidate) in an election or representative body.
- 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_69e245884860819081046ce07d5872c4 |
completed | April 17, 2026, 2:36 p.m. |
| NER | Named-entity recognition | batch_69f167e75658819089153eab7563540c |
completed | April 29, 2026, 2:07 a.m. |
| PD | Predicate disambiguation | batch_69ee627be4248190889a88764624e174 |
completed | April 26, 2026, 7:07 p.m. |
Created at: April 17, 2026, 2:54 p.m.