Triple
T24693206
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | China Camp Village |
E611501
|
entity |
| Predicate | hasHistoricPhotographsOnDisplay |
P157183
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [China Camp Village, hasHistoricPhotographsOnDisplay, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasHistoricPhotographsOnDisplay Context triple: [China Camp Village, hasHistoricPhotographsOnDisplay, yes]
-
A.
hasPhotographs
Indicates that one entity possesses, contains, or is associated with one or more photographs of another entity or subject.
-
B.
hasPhotographicRecordSince
Indicates that a photographic record of an entity has existed continuously since a specified point in time.
-
C.
hasPhotographicCollectionAt
Indicates that an entity maintains or possesses a photographic collection located at a specified place or institution.
-
D.
hasPhotograph
Indicates that one entity possesses, includes, or is associated with a photograph depicting or representing another entity.
-
E.
hasPhotographicSignificance
Indicates that something holds notable importance or relevance in the context of photography, such as for documentation, artistic value, or visual record.
- 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_69e2c4d678b081908910f4271627a31a |
completed | April 17, 2026, 11:40 p.m. |
| NER | Named-entity recognition | batch_69f422aee0408190899efe7e24ef2b40 |
completed | May 1, 2026, 3:49 a.m. |
| PD | Predicate disambiguation | batch_69f420e92cc88190a803aecdae78a051 |
completed | May 1, 2026, 3:41 a.m. |
| PDg | Predicate description generation | batch_69f422add8508190a76e56cfa756eeb8 |
completed | May 1, 2026, 3:49 a.m. |
Created at: April 18, 2026, 3:21 a.m.