Triple
T6535795
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Asian Project Market |
E152358
|
entity |
| Predicate | benefitsForFilmmakers |
P71498
|
FINISHED |
| Object | access to international financing |
—
|
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: access to international financing | Statement: [Asian Project Market, benefitsForFilmmakers, access to international financing]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: benefitsForFilmmakers Context triple: [Asian Project Market, benefitsForFilmmakers, access to international financing]
-
A.
independentFilm
Indicates that a film is produced outside the major studio system, typically with greater creative control and lower budgets.
-
B.
filmicFunction
Indicates the role or purpose that something serves within the structure, style, or narrative function of a film.
-
C.
filmEditingAcademyAward
Indicates that an entity received or is associated with an Academy Award specifically for film editing.
-
D.
cinematographyAwardedTo
Indicates that a cinematography-related award has been given to a particular recipient (such as a person or team) for their work.
-
E.
bestLiveActionShortFilmWinner
Indicates that the subject is the winner of the Best Live Action Short Film award in a given year or context.
- 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_69c688048ec8819093a47f7d332e12ec |
completed | March 27, 2026, 1:37 p.m. |
| NER | Named-entity recognition | batch_69c6adc238688190aca143b22b8a399c |
completed | March 27, 2026, 4:18 p.m. |
| PD | Predicate disambiguation | batch_69c68abd9c7c819099e4fe8097cd1b28 |
completed | March 27, 2026, 1:48 p.m. |
| PDg | Predicate description generation | batch_69c69f362ee4819090e8fa48caef7d7d |
completed | March 27, 2026, 3:16 p.m. |
Created at: March 27, 2026, 1:46 p.m.