Triple
T8532221
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Christine Falls |
E201979
|
entity |
| Predicate | isPhotographed |
P9792
|
FINISHED |
| Object | frequently |
—
|
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: frequently | Statement: [Christine Falls, isPhotographed, frequently]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isPhotographed Context triple: [Christine Falls, isPhotographed, frequently]
-
A.
hasPhotograph
Indicates that one entity possesses, includes, or is associated with a photograph depicting or representing another entity.
-
B.
hasPhotoOn
Indicates that one entity has an associated photograph stored, displayed, or linked on another entity (such as a platform, page, or medium).
-
C.
hasPhotographicRecordSince
Indicates that a photographic record of an entity has existed continuously since a specified point in time.
-
D.
isPhotographicSubject
chosen
Indicates that an entity serves as the subject or main focus captured in a photograph taken by another entity.
-
E.
hasPhotoSpot
Indicates that a location or entity includes or is associated with a designated place suitable for taking photographs.
- 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_69ca832355b08190b8b6a4ab4a4a3554 |
completed | March 30, 2026, 2:05 p.m. |
| NER | Named-entity recognition | batch_69cbe676e2ac8190b65a3d2a935776fd |
completed | March 31, 2026, 3:21 p.m. |
| PD | Predicate disambiguation | batch_69cbd111bf988190be98c92a607c6456 |
completed | March 31, 2026, 1:50 p.m. |
Created at: March 30, 2026, 6:17 p.m.