Triple
T27034022
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Miss Universe 1987 |
E681002
|
entity |
| Predicate | missPhotogenicWinner |
P161790
|
FINISHED |
| Object | Patricia López Ruiz |
—
|
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: Patricia López Ruiz | Statement: [Miss Universe 1987, missPhotogenicWinner, Patricia López Ruiz]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: missPhotogenicWinner Context triple: [Miss Universe 1987, missPhotogenicWinner, Patricia López Ruiz]
-
A.
hasPhotogenicFeature
Indicates that an entity possesses a visual characteristic or attribute that is especially attractive or appealing when photographed.
-
B.
hasPhotoSpot
Indicates that a location or entity includes or is associated with a designated place suitable for taking photographs.
-
C.
shotFrom
Indicates that something is propelled or discharged starting at a particular source or origin.
-
D.
shotOn
Indicates that one entity fired or took a shot at another entity, typically in a sports or combat context.
-
E.
isPhotographicSubject
Indicates that an entity serves as the subject or main focus captured in a photograph taken by another entity.
- 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_69f6223870308190a016b76902bcf6d4 |
completed | May 2, 2026, 4:11 p.m. |
| PD | Predicate disambiguation | batch_69f61b3ee7b08190a0a1bc5d26b757aa |
completed | May 2, 2026, 3:41 p.m. |
| PDg | Predicate description generation | batch_69f61f109ef48190873bfe18638d2046 |
completed | May 2, 2026, 3:58 p.m. |
Created at: April 27, 2026, 7:15 a.m.