Triple
T27034031
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Miss Universe 1987 |
E681002
|
entity |
| Predicate | fourthRunnerUpCountry |
P165378
|
FINISHED |
| Object | Philippines |
—
|
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: Philippines | Statement: [Miss Universe 1987, fourthRunnerUpCountry, Philippines]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: fourthRunnerUpCountry Context triple: [Miss Universe 1987, fourthRunnerUpCountry, Philippines]
-
A.
thirdPlaceCountry
Indicates the country that finished in third place in a given competition or ranking.
-
B.
thirdWinnerCountry
Indicates the country associated with the entity that placed third in a competition or ranking.
-
C.
finalFourCountry
Indicates that a country’s team reached the semifinal (Final Four) stage of a given tournament or competition.
-
D.
fifthWinnerCountry
Indicates the country associated with the entity that finished in fifth place in a competition or ranking.
-
E.
fourthPlace
Indicates that an entity holds the fourth position or rank in an ordered sequence, competition, or hierarchy.
- F. None of above. chosen
Provenance (4 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_69f658a91ba0819084fbe3dd8a09f7cd |
completed | May 2, 2026, 8:03 p.m. |
| PD | Predicate disambiguation | batch_69f6575ba12081909396036f78757a76 |
completed | May 2, 2026, 7:58 p.m. |
| PDg | Predicate description generation | batch_69f657f2c8b08190bfeb3173ef78207d |
completed | May 2, 2026, 8 p.m. |
Created at: April 27, 2026, 7:15 a.m.