Triple
T6959253
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Indican Pictures |
E161326
|
entity |
| Predicate | distributedFilmGenre |
P73772
|
FINISHED |
| Object | crime thriller |
—
|
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: crime thriller | Statement: [Indican Pictures, distributedFilmGenre, crime thriller]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distributedFilmGenre Context triple: [Indican Pictures, distributedFilmGenre, crime thriller]
-
A.
distributedFilmType
Indicates that a film was distributed in a particular format or category of distribution.
-
B.
distributedFilm
Indicates that one entity served as the distributor responsible for releasing or circulating a particular film.
-
C.
keyGenreFilm
Indicates that a particular genre is the primary or defining genre associated with a given film.
-
D.
filmType
Indicates the specific category or genre that a film belongs to.
-
E.
filmBase
Indicates the primary location or headquarters from which a film-related entity (such as a production, company, or operation) is based or operates.
- 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_69c68852a9a0819097797e31d492e273 |
completed | March 27, 2026, 1:38 p.m. |
| NER | Named-entity recognition | batch_69c6daedbb4c8190b46846fb1265b937 |
completed | March 27, 2026, 7:30 p.m. |
| PD | Predicate disambiguation | batch_69c6d7c0b0a08190b262dfc94992994d |
completed | March 27, 2026, 7:17 p.m. |
| PDg | Predicate description generation | batch_69c6d9bb57e88190a3a7cec34e3b617f |
completed | March 27, 2026, 7:25 p.m. |
Created at: March 27, 2026, 2:29 p.m.