Triple
T36517901
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rand Paul presidential campaign, 2016 |
E900096
|
entity |
| Predicate | candidatePartyAffiliation |
P114263
|
FINISHED |
| Object | Republican Party |
—
|
NE NERFINISHED |
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: Republican Party | Statement: [Rand Paul presidential campaign, 2016, candidatePartyAffiliation, Republican Party]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: candidatePartyAffiliation Context triple: [Rand Paul presidential campaign, 2016, candidatePartyAffiliation, Republican Party]
-
A.
holderPoliticalAffiliation
Indicates that a person or officeholder is associated with or belongs to a particular political party or ideology.
-
B.
partnerPoliticalAffiliation
Indicates that one entity has a political affiliation that is associated with, or shared by, its partner entity.
-
C.
subjectPoliticalParty
chosen
Indicates the political party with which the subject is formally affiliated or identified.
-
D.
partyAffiliationOrStatus
Indicates the political party with which an entity is associated or the entity’s current standing or role within that party.
-
E.
partyAffiliationOfPetitioner
Indicates the political party with which the petitioner is affiliated.
- 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_69f76e5dada881909da2d34bc7a9202a |
completed | May 3, 2026, 3:48 p.m. |
| NER | Named-entity recognition | batch_69f7c777e924819081a6634f549fe552 |
completed | May 3, 2026, 10:08 p.m. |
| PD | Predicate disambiguation | batch_69f7c477a4d481908f52e55b6688f60c |
completed | May 3, 2026, 9:56 p.m. |
Created at: May 3, 2026, 4:11 p.m.