Triple
T7711576
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Peter S. Elliot |
E174769
|
entity |
| Predicate | occupationField |
P24248
|
FINISHED |
| Object | film industry |
—
|
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: film industry | Statement: [Peter S. Elliot, occupationField, film industry]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: occupationField Context triple: [Peter S. Elliot, occupationField, film industry]
-
A.
occupationType
Indicates the specific kind or category of work, profession, or role that an entity performs or holds.
-
B.
careerField
chosen
Indicates the professional domain or occupational area in which an entity works or specializes.
-
C.
subjectOccupation
Indicates that the subject holds or performs a particular job, profession, or role as their occupation.
-
D.
traditionalOccupations
Indicates that an entity is associated with occupations or jobs that are customary, long-established, or culturally traditional within a particular community or context.
-
E.
requiredOccupationOf
Indicates that one entity specifies the occupation or job role that is required or expected for another entity (such as a position, task, or qualification).
- 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_69c6995b3e8c8190833108f883d5f53c |
completed | March 27, 2026, 2:51 p.m. |
| NER | Named-entity recognition | batch_69c702ebb7448190ae8d47fe0cbb0907 |
completed | March 27, 2026, 10:21 p.m. |
| PD | Predicate disambiguation | batch_69c701683dec8190be9861e592aa8ce0 |
completed | March 27, 2026, 10:15 p.m. |
Created at: March 27, 2026, 4:04 p.m.