Triple
T567738
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 2021 Chilean presidential election |
E13591
|
entity |
| Predicate | secondRoundTurnoutApprox |
P1234
|
FINISHED |
| Object | 56% |
—
|
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: 56% | Statement: [2021 Chilean presidential election, secondRoundTurnoutApprox, 56%]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: secondRoundTurnoutApprox Context triple: [2021 Chilean presidential election, secondRoundTurnoutApprox, 56%]
-
A.
voterTurnoutPercentage
chosen
Indicates the proportion of eligible or registered voters who actually cast a ballot in a given election, expressed as a percentage.
-
B.
popularVoteRunnerUp
Indicates that one entity is the candidate who received the second-highest number of votes in a popular vote for the other entity’s election or contest.
-
C.
secondPhase
Indicates that an entity is in, or has progressed to, the second phase or stage of a multi-phase process or sequence.
-
D.
voterTurnoutChange
Indicates the amount or direction of change in voter turnout between two elections or time periods.
-
E.
referendumResultRemainPercentage
Indicates the percentage of votes in a referendum that were cast in favor of remaining (as opposed to leaving or changing the status quo).
- 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_69a4933edcf08190b35ecfd6014caee6 |
completed | March 1, 2026, 7:27 p.m. |
| NER | Named-entity recognition | batch_69a49b02da148190b6a9bad3a22d8ec5 |
completed | March 1, 2026, 8:01 p.m. |
| PD | Predicate disambiguation | batch_69a494c183b081909304944aa3d0fe8f |
completed | March 1, 2026, 7:34 p.m. |
Created at: March 1, 2026, 7:33 p.m.