Triple
T24384831
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Metro-Goldwyn-Mayer contract players |
E614716
|
entity |
| Predicate | notableEmployerFeature |
P156000
|
FINISHED |
| Object | star system |
—
|
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: star system | Statement: [Metro-Goldwyn-Mayer contract players, notableEmployerFeature, star system]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: notableEmployerFeature Context triple: [Metro-Goldwyn-Mayer contract players, notableEmployerFeature, star system]
-
A.
notableEmployer
Indicates that an entity has been employed by, or has worked for, a particularly significant or noteworthy organization or individual.
-
B.
notableEnterprise
Indicates that an entity is a business or commercial organization recognized for its significance, prominence, or impact.
-
C.
employerOnNotableWork
Indicates that the specified employer is associated with or responsible for the notable work in which the other entity is involved.
-
D.
notableBusinessType
Indicates that an entity is notably associated with, characterized by, or best known for a particular type of business.
-
E.
notableIndustry
Indicates that an entity is significantly recognized or prominent within a specified industry or sector.
- F. None of above. chosen
Provenance (4 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_69e2d7e362e481909e32fe4ef8269d4f |
completed | April 18, 2026, 1:01 a.m. |
| NER | Named-entity recognition | batch_69f294540000819099bacb398a36204f |
completed | April 29, 2026, 11:29 p.m. |
| PD | Predicate disambiguation | batch_69f287c4a2b48190b80fb7a3c0e9b018 |
completed | April 29, 2026, 10:35 p.m. |
| PDg | Predicate description generation | batch_69f28f4d978c81908310c01def2514cc |
completed | April 29, 2026, 11:07 p.m. |
Created at: April 18, 2026, 2:03 a.m.