Triple
T34148532
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Zimbabwean presidential election, 1996 |
E875929
|
entity |
| Predicate | percentageVoteWinner |
P36641
|
FINISHED |
| Object | 92.7% |
—
|
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: 92.7% | Statement: [Zimbabwean presidential election, 1996, percentageVoteWinner, 92.7%]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: percentageVoteWinner Context triple: [Zimbabwean presidential election, 1996, percentageVoteWinner, 92.7%]
-
A.
hasPopularVotePercentageForWinner
chosen
Indicates the percentage of the total popular vote received by the winning candidate or option in an election or vote.
-
B.
opponentPopularVotePercentage
Indicates the percentage of the total popular vote received by the opposing candidate or party in an election.
-
C.
smithPopularVotePercentage
Indicates the percentage of the popular vote that was received by the entity named Smith in a given election or voting context.
-
D.
popularVotePercentageLoser
Indicates the percentage of the total popular vote received by the candidate or party that did not win the election.
-
E.
popularVoteWinner
Indicates that the subject is the candidate who received the highest number of individual votes cast by the electorate in an election.
- 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_69f349abaa508190a820f206620efddc |
completed | April 30, 2026, 12:23 p.m. |
| NER | Named-entity recognition | batch_69f7234bcaa48190ac970759d34e254a |
completed | May 3, 2026, 10:28 a.m. |
| PD | Predicate disambiguation | batch_69f72155c48881909bd40b9aa3febd5a |
completed | May 3, 2026, 10:20 a.m. |
Created at: May 1, 2026, 1:54 a.m.