Triple
T27034028
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Miss Universe 1987 |
E681002
|
entity |
| Predicate | thirdRunnerUp |
P35718
|
FINISHED |
| Object | Inés María Calero |
—
|
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: Inés María Calero | Statement: [Miss Universe 1987, thirdRunnerUp, Inés María Calero]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: thirdRunnerUp Context triple: [Miss Universe 1987, thirdRunnerUp, Inés María Calero]
-
A.
secondRunnerUp
Indicates that one entity finished in third place in a competition or ranking relative to the others.
-
B.
secondRoundRunnerUp
Indicates that an entity finished in third place (runner-up to the runner-up) in the second round of a competition or selection process.
-
C.
thirdPlaceTeam
Indicates that a team finished in third place in a competition, league, or ranking.
-
D.
thirdPlaceCandidate
chosen
Indicates that the subject is the candidate who finished in third place in a competition, ranking, or election.
-
E.
conferenceOfRunnerUp
Indicates the conference or league affiliation to which the runner-up entity belongs.
- 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_69eeeb5566f08190813daf896fa3da04 |
completed | April 27, 2026, 4:51 a.m. |
| NER | Named-entity recognition | batch_69f6a28c7c148190bfc980aad9f678ca |
completed | May 3, 2026, 1:19 a.m. |
| PD | Predicate disambiguation | batch_69f69fe1e3c88190830bb2e9f407357e |
completed | May 3, 2026, 1:07 a.m. |
Created at: April 27, 2026, 7:15 a.m.