Triple
T25517985
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | South Carolina Democratic primary |
E639560
|
entity |
| Predicate | winner2016 |
P136441
|
FINISHED |
| Object | Hillary Clinton |
—
|
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: Hillary Clinton | Statement: [South Carolina Democratic primary, winner2016, Hillary Clinton]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: winner2016 Context triple: [South Carolina Democratic primary, winner2016, Hillary Clinton]
-
A.
has2020Winner
Indicates that a given competition, award, or event is associated with the entity that won it in the year 2020.
-
B.
2016Winner
chosen
Indicates that the subject is the entity that won a specified competition, award, or event in the year 2016.
-
C.
electionWinner
Indicates that the subject is the candidate who received the highest support and officially won a particular election.
-
D.
ranPresidentialCandidate
Indicates that the subject has been a candidate in a presidential election.
-
E.
electedCandidate
Indicates that a particular person has been chosen as the winner in an election for a given position or office.
- 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_69e75dbe32e48190a62d749a0ff2a96a |
completed | April 21, 2026, 11:21 a.m. |
| NER | Named-entity recognition | batch_69f5f8339a8081908738ba23158091c9 |
completed | May 2, 2026, 1:12 p.m. |
| PD | Predicate disambiguation | batch_69f4a0f7c6008190ae8cee3e71e19b94 |
completed | May 1, 2026, 12:47 p.m. |
Created at: April 21, 2026, 2:57 p.m.