Triple
T6709719
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Paul J. Smith |
E153103
|
entity |
| Predicate | notableEmployerType |
P35312
|
FINISHED |
| Object | major American film studio |
—
|
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: major American film studio | Statement: [Paul J. Smith, notableEmployerType, major American film studio]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: notableEmployerType Context triple: [Paul J. Smith, notableEmployerType, major American film studio]
-
A.
notableEmployer
Indicates that an entity has been employed by, or has worked for, a particularly significant or noteworthy organization or individual.
-
B.
notableBusinessType
chosen
Indicates that an entity is notably associated with, characterized by, or best known for a particular type of business.
-
C.
notableEnterprise
Indicates that an entity is a business or commercial organization recognized for its significance, prominence, or impact.
-
D.
notableIndustry
Indicates that an entity is significantly recognized or prominent within a specified industry or sector.
-
E.
employerType
Indicates the classification or category of an employer in relation to the entity (e.g., public, private, nonprofit, self-employed).
- 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_69c68808d8d8819087369015270788fe |
completed | March 27, 2026, 1:37 p.m. |
| NER | Named-entity recognition | batch_69c6d16897e48190b43eda2206b14d6a |
completed | March 27, 2026, 6:50 p.m. |
| PD | Predicate disambiguation | batch_69c6d089c7488190a00853fb12f53b2a |
completed | March 27, 2026, 6:46 p.m. |
Created at: March 27, 2026, 2:06 p.m.