Triple
T38671149
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Libra Films International |
E940591
|
entity |
| Predicate | typeOfFilmsHandled |
P136433
|
FINISHED |
| Object | foreign-language 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: foreign-language films | Statement: [Libra Films International, typeOfFilmsHandled, foreign-language films]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typeOfFilmsHandled Context triple: [Libra Films International, typeOfFilmsHandled, foreign-language films]
-
A.
workFilmType
chosen
Indicates the type or category of film associated with a particular work.
-
B.
producedFilmType
Indicates that an entity (such as a person or organization) was responsible for producing a film of a specified type or category.
-
C.
cinemaType
Indicates the specific category or kind of cinema associated with an entity (e.g., multiplex, art house, drive-in).
-
D.
featuredInFilmGenre
Indicates that an entity (such as a film, character, or work) appears in or is associated with a specific film genre.
-
E.
distributedFilmType
Indicates that a film was distributed in a particular format or category of distribution.
- 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_69f76edfde348190bf6529d9f49ecd62 |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_6a037c9141dc819098d7fcc36e69882c |
completed | May 12, 2026, 7:16 p.m. |
| PD | Predicate disambiguation | batch_6a037a2026248190b894436a578d79ac |
completed | May 12, 2026, 7:06 p.m. |
Created at: May 3, 2026, 4:33 p.m.