Triple
T31336272
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ba Vì ancient church ruins |
E799179
|
entity |
| Predicate | photogenicFor |
P121927
|
FINISHED |
| Object | wedding photography |
—
|
LITERAL FINISHED |
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: wedding photography | Statement: [Ba Vì ancient church ruins, photogenicFor, wedding photography]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: photogenicFor Context triple: [Ba Vì ancient church ruins, photogenicFor, wedding photography]
-
A.
hasPhotogenicFeature
chosen
Indicates that an entity possesses a visual characteristic or attribute that is especially attractive or appealing when photographed.
-
B.
isPhotographicSubject
Indicates that an entity serves as the subject or main focus captured in a photograph taken by another entity.
-
C.
usesPhotographyFrom
Indicates that one entity employs or incorporates photographic material originating from another entity.
-
D.
missPhotogenicWinner
Indicates that an entity is the winner of a Miss Photogenic title or award in a given context.
-
E.
isFrequentlyPhotographedAs
Indicates that one entity is commonly or repeatedly depicted in photographs in the role, appearance, or identity of another entity.
- 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_69f224e3f6ac8190a13488516abca7c9 |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_69f6a916d2e08190bafc01cba73b6469 |
completed | May 3, 2026, 1:47 a.m. |
| PD | Predicate disambiguation | batch_69f6a7548eb48190a69b60a3c6ad53b9 |
completed | May 3, 2026, 1:39 a.m. |
Created at: April 29, 2026, 9:16 p.m.