Triple
T33799012
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Miss World 1967 |
E866158
|
entity |
| Predicate | hadContestant |
P46216
|
FINISHED |
| Object | Shakira Caine |
—
|
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: Shakira Caine | Statement: [Miss World 1967, hadContestant, Shakira Caine]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hadContestant Context triple: [Miss World 1967, hadContestant, Shakira Caine]
-
A.
contestantOn
chosen
Indicates that one entity participates as a competitor in a contest, show, or competition associated with another entity.
-
B.
hadChampionshipContender
Indicates that an entity possessed or was associated with a competitor or team that was seriously in contention to win a championship.
-
C.
losesContestTo
Indicates that one participant is defeated by another in a contest or competition.
-
D.
hasFormerParticipant
Indicates that an entity once participated in an activity, event, or organization but is no longer a current participant.
-
E.
hadMember
Indicates that an entity was formerly a member or part of another entity or group.
- 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_69f3498f99f481909cb271f4965a7594 |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_69f6ffbad8848190867c2988c0ceb84f |
completed | May 3, 2026, 7:56 a.m. |
| PD | Predicate disambiguation | batch_69f6fc59518081908b0275f47721d561 |
completed | May 3, 2026, 7:42 a.m. |
Created at: May 1, 2026, 1:46 a.m.