Triple
T27034021
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Miss Universe 1987 |
E681002
|
entity |
| Predicate | missCongenialityWinnerCountry |
P40096
|
FINISHED |
| Object | Spain |
—
|
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: Spain | Statement: [Miss Universe 1987, missCongenialityWinnerCountry, Spain]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: missCongenialityWinnerCountry Context triple: [Miss Universe 1987, missCongenialityWinnerCountry, Spain]
-
A.
missCongenialityWinner
Indicates that the subject is the winner of a "Miss Congeniality" title or award in a given context or event.
-
B.
nationalityOfWinner
chosen
Indicates the country or nationality associated with the winner of a given event or competition.
-
C.
winnerCountry
Indicates the country that achieved first place or victory in a given competition, event, or contest.
-
D.
locationCountryOfCeremony
Indicates the country in which a particular ceremony takes place or is held.
-
E.
countryOf
Indicates that one entity is the country to which another entity belongs, is located in, or is associated with.
- 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_69f6223870308190a016b76902bcf6d4 |
completed | May 2, 2026, 4:11 p.m. |
| PD | Predicate disambiguation | batch_69f620e0b37481909a280574decbd443 |
completed | May 2, 2026, 4:05 p.m. |
Created at: April 27, 2026, 7:15 a.m.