Triple
T4803069
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Old Well |
E106880
|
entity |
| Predicate | isPhotographedBy |
P12333
|
FINISHED |
| Object | students |
—
|
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: students | Statement: [Old Well, isPhotographedBy, students]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isPhotographedBy Context triple: [Old Well, isPhotographedBy, students]
-
A.
hasPhotograph
Indicates that one entity possesses, includes, or is associated with a photograph depicting or representing another entity.
-
B.
imagedBy
Indicates that something is captured, recorded, or represented in an image created by a particular imaging device, method, or agent.
-
C.
photographer
chosen
Indicates that one entity takes photographs of another entity, typically in a professional or intentional capacity.
-
D.
photographedByTourists
Indicates that the subject has been photographed by people visiting as tourists.
-
E.
notablePhotographer
Indicates that the subject is a photographer who is recognized as notable or significant in some context.
- 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_69bd43f6a1e08190bf0a372bfc336ee5 |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd6ff981fc819080d4466c6fe06cf3 |
completed | March 20, 2026, 4:04 p.m. |
| PD | Predicate disambiguation | batch_69bd6c1c43a48190a65e56b1624a2339 |
completed | March 20, 2026, 3:47 p.m. |
Created at: March 20, 2026, 1:23 p.m.