Triple
T28812073
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 2016 Beninese presidential election |
E727538
|
entity |
| Predicate | secondRoundVoteShareOfRunnerUp |
P47100
|
FINISHED |
| Object | 34.63% |
—
|
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: 34.63% | Statement: [2016 Beninese presidential election, secondRoundVoteShareOfRunnerUp, 34.63%]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: secondRoundVoteShareOfRunnerUp Context triple: [2016 Beninese presidential election, secondRoundVoteShareOfRunnerUp, 34.63%]
-
A.
secondRoundVoteShareOf
Indicates the proportion of total votes an entity receives in the second round of a multi-round voting or election process.
-
B.
secondRoundRunnerUpVoteSharePercentage
chosen
Indicates the percentage of total votes received by the candidate who finished as runner-up in the second round of a contest or election.
-
C.
runnerUpVoteSharePercentage
Indicates the percentage of total votes received by the candidate or option that finished in second place.
-
D.
secondPartyPopularVoteShare
Indicates the proportion of total popular votes received by the second party in an election.
-
E.
secondRoundRunnerUp
Indicates that an entity finished in third place (runner-up to the runner-up) in the second round of a competition or selection process.
- 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_69f0319c38948190bca746ad60fd25ba |
completed | April 28, 2026, 4:03 a.m. |
| NER | Named-entity recognition | batch_69fcf825ca7081909d06b0df33eb33f9 |
completed | May 7, 2026, 8:37 p.m. |
| PD | Predicate disambiguation | batch_69fcf42160f0819096812a8bf590875e |
completed | May 7, 2026, 8:20 p.m. |
Created at: April 28, 2026, 6:31 a.m.