Triple
T17646906
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bush–Cheney 2000 campaign |
E429380
|
entity |
| Predicate | presidentialNomineeOccupation |
P29120
|
FINISHED |
| Object | Governor of Texas |
—
|
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: Governor of Texas | Statement: [Bush–Cheney 2000 campaign, presidentialNomineeOccupation, Governor of Texas]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: presidentialNomineeOccupation Context triple: [Bush–Cheney 2000 campaign, presidentialNomineeOccupation, Governor of Texas]
-
A.
officeHolderOccupation
Indicates that the occupation describes the role or job held by an office holder.
-
B.
professionOfCandidate
chosen
Indicates that one entity is the profession or occupational role held by the candidate entity.
-
C.
partyPresidentialNomineeOf
Indicates that a person is the officially selected presidential nominee representing a particular political party.
-
D.
ranPresidentialCandidate
Indicates that the subject has been a candidate in a presidential election.
-
E.
notablePresidentialCandidate
Indicates that a person has been a prominent or widely recognized candidate in a presidential 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_69d889e2c2608190b762e76d9b2262f1 |
completed | April 10, 2026, 5:25 a.m. |
| NER | Named-entity recognition | batch_69e46e39937881909bb6a1792fff39a9 |
completed | April 19, 2026, 5:55 a.m. |
| PD | Predicate disambiguation | batch_69e3cddc87188190ac2f049b86038676 |
completed | April 18, 2026, 6:30 p.m. |
Created at: April 10, 2026, 6:04 a.m.