Triple
T5002370
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 摺鉢山 |
E112402
|
entity |
| Predicate | 有名な写真 |
P34247
|
FINISHED |
| Object | 硫黄島の星条旗掲揚 |
—
|
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: 硫黄島の星条旗掲揚 | Statement: [摺鉢山, 有名な写真, 硫黄島の星条旗掲揚]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: 有名な写真 Context triple: [摺鉢山, 有名な写真, 硫黄島の星条旗掲揚]
-
A.
famousImage
chosen
Indicates that an image is widely recognized or well-known, typically due to its prominence, popularity, or cultural significance.
-
B.
notablePhotographer
Indicates that the subject is a photographer who is recognized as notable or significant in some context.
-
C.
hasPhotographicSignificance
Indicates that something holds notable importance or relevance in the context of photography, such as for documentation, artistic value, or visual record.
-
D.
isPhotographicSubject
Indicates that an entity serves as the subject or main focus captured in a photograph taken by another entity.
-
E.
hasPhotograph
Indicates that one entity possesses, includes, or is associated with a photograph depicting or representing 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_69bd4433d0b08190877e83959ef40d81 |
completed | March 20, 2026, 12:57 p.m. |
| NER | Named-entity recognition | batch_69bd7472a1dc8190942f568a81fdd961 |
completed | March 20, 2026, 4:23 p.m. |
| PD | Predicate disambiguation | batch_69bd714aee2481908fb0dd5fa2daf3a1 |
completed | March 20, 2026, 4:09 p.m. |
Created at: March 20, 2026, 1:34 p.m.