Triple
T11232292
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | A Choice of Weapons |
E265850
|
entity |
| Predicate | hasAuthorOccupationOfSubject |
P85131
|
FINISHED |
| Object | photographer |
—
|
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: photographer | Statement: [A Choice of Weapons, hasAuthorOccupationOfSubject, photographer]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasAuthorOccupationOfSubject Context triple: [A Choice of Weapons, hasAuthorOccupationOfSubject, photographer]
-
A.
authorOccupation
Indicates the professional role or job that an author holds or is associated with.
-
B.
hasBiographicalSubjectOccupation
chosen
Indicates that the biographical subject is or was engaged in the specified occupation or profession.
-
C.
hasAuthorRelationshipToSubject
Indicates that an entity serves as the author or creator of the specified subject.
-
D.
hasAuthorEmployer
Indicates that the specified organization or entity is the employer of the author in question.
-
E.
workAuthorIs
Indicates that a specific person or entity is the author or creator of a particular work.
- 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_69d6aac656d48190b275efaa7d6074ee |
completed | April 8, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69d7e9026e1c81909456ac946bbba972 |
completed | April 9, 2026, 5:59 p.m. |
| PD | Predicate disambiguation | batch_69d75cfdf7a88190aae21572e57ef208 |
completed | April 9, 2026, 8:02 a.m. |
Created at: April 8, 2026, 9:30 p.m.