Triple
T8801091
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Be Gentlemen Limited Partnership |
E209407
|
entity |
| Predicate | workGenreAssociated |
P14417
|
FINISHED |
| Object | drama films |
—
|
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: drama films | Statement: [Be Gentlemen Limited Partnership, workGenreAssociated, drama films]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: workGenreAssociated Context triple: [Be Gentlemen Limited Partnership, workGenreAssociated, drama films]
-
A.
belongsToWorkGenre
Indicates that a creative work is classified under or associated with a particular genre.
-
B.
genreAssociatedWith
Indicates a relationship where a work, item, or entity is linked to or categorized under a particular genre.
-
C.
workedOnGenre
chosen
Indicates that an entity (such as a person or organization) has done work related to a particular genre.
-
D.
genreOfAssociatedPerson
Indicates that a particular genre is associated with a given person, such as an artist, author, or performer.
-
E.
hasGenreInRoles
Indicates that an entity participates in roles associated with a particular genre or set of genres.
- 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_69ca836320e48190b5cf585b90a322c4 |
completed | March 30, 2026, 2:06 p.m. |
| NER | Named-entity recognition | batch_69cc5fb8aab88190befed16301e08efc |
completed | March 31, 2026, 11:58 p.m. |
| PD | Predicate disambiguation | batch_69cc5c1f28ec8190a34311cb412920c2 |
completed | March 31, 2026, 11:43 p.m. |
Created at: March 30, 2026, 6:44 p.m.