Triple
T33254787
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bob Dole presidential campaign |
E851345
|
entity |
| Predicate | opponentElectoralVoteCount |
P9221
|
FINISHED |
| Object | 379 |
—
|
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: 379 | Statement: [Bob Dole presidential campaign, opponentElectoralVoteCount, 379]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: opponentElectoralVoteCount Context triple: [Bob Dole presidential campaign, opponentElectoralVoteCount, 379]
-
A.
opponentElectoralVotes
chosen
Indicates the number of electoral votes received by the opposing candidate or party in an election.
-
B.
electoralVoteFor
Indicates that a specified number of electoral votes are allocated or cast in favor of a particular candidate or option in an election.
-
C.
electoralVotesReceived
Indicates that one entity received a specified number of electoral votes in an election from another entity or jurisdiction.
-
D.
electoralVotesWinner
Indicates that the subject is the candidate who received the highest number of electoral votes in a given election.
-
E.
popularVoteCountOpponent
Indicates the number of votes received by the opposing candidate or party in a popular vote contest.
- 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_69f34963135c819084e7f1d483421f00 |
completed | April 30, 2026, 12:21 p.m. |
| NER | Named-entity recognition | batch_69f6ffbad8848190867c2988c0ceb84f |
completed | May 3, 2026, 7:56 a.m. |
| PD | Predicate disambiguation | batch_69f6fc5740fc81909774a4f65201a3ff |
completed | May 3, 2026, 7:42 a.m. |
Created at: May 1, 2026, 1:31 a.m.