Triple
T25507043
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 2019 Istanbul mayoral election (June) |
E639270
|
entity |
| Predicate | voteShareLoser |
P6370
|
FINISHED |
| Object | approximately 45.0% |
—
|
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: approximately 45.0% | Statement: [2019 Istanbul mayoral election (June), voteShareLoser, approximately 45.0%]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: voteShareLoser Context triple: [2019 Istanbul mayoral election (June), voteShareLoser, approximately 45.0%]
-
A.
popularVoteLoserTotal
Indicates that the subject is the candidate who lost the election overall but received the specified total number of popular votes.
-
B.
popularVoteLoser
Indicates that the subject became the winner of an election despite receiving fewer popular votes than at least one opponent.
-
C.
popularVoteLoserParty
Indicates that the subject is the political party of a candidate who lost the popular vote in an election.
-
D.
popularVotePercentageLoser
chosen
Indicates the percentage of the total popular vote received by the candidate or party that did not win the election.
-
E.
hasPopularVoteForLoser
Indicates that in a given election, the candidate who lost the overall contest nonetheless received the majority of the popular vote.
- 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_69e75dbd09308190b6b5f0afdc12ec6d |
completed | April 21, 2026, 11:21 a.m. |
| NER | Named-entity recognition | batch_69f5f806927881908443eaf9584c11b1 |
completed | May 2, 2026, 1:11 p.m. |
| PD | Predicate disambiguation | batch_69f468421ba08190880eac99135e5970 |
completed | May 1, 2026, 8:45 a.m. |
Created at: April 21, 2026, 2:47 p.m.