Triple
T11232358
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Fort Scott High School |
E265852
|
entity |
| Predicate | GordonParksOccupation |
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: [Fort Scott High School, GordonParksOccupation, photographer]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: GordonParksOccupation Context triple: [Fort Scott High School, GordonParksOccupation, photographer]
-
A.
cinematographerOfWork
Indicates that a person served as the cinematographer (director of photography) for a specific creative work.
-
B.
authorOccupation
Indicates the professional role or job that an author holds or is associated with.
-
C.
partOfCreativeCareerOf
Indicates that one entity represents a work, role, or activity that forms a component or phase within another entity’s overall creative career.
-
D.
hasBiographicalSubjectOccupation
chosen
Indicates that the biographical subject is or was engaged in the specified occupation or profession.
-
E.
businessRoleOfJudyGarland
Indicates the specific business-related role or capacity that Judy Garland holds in relation to another entity or activity.
- 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.