Triple
T34249974
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Academy Award for Best Foreign Language Film (for Amarcord film) |
E878711
|
entity |
| Predicate | filmGenreAwarded |
P13422
|
FINISHED |
| Object | comedy-drama |
—
|
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: comedy-drama | Statement: [Academy Award for Best Foreign Language Film (for Amarcord film), filmGenreAwarded, comedy-drama]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: filmGenreAwarded Context triple: [Academy Award for Best Foreign Language Film (for Amarcord film), filmGenreAwarded, comedy-drama]
-
A.
filmGenreOfRelatedWork
Indicates that a work is related to another work through sharing or being associated with the same film genre.
-
B.
filmAdaptationAward
Indicates that an award is given specifically in recognition of a film adaptation of an existing work.
-
C.
featuredInFilmGenre
Indicates that an entity (such as a film, character, or work) appears in or is associated with a specific film genre.
-
D.
filmAdaptationGenre
Indicates that a film adaptation belongs to or is categorized under a particular genre.
-
E.
genreOfAwards
chosen
Indicates the type or category of awards associated with a given work, event, or entity.
- 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_69f349b3618481909df955b063f305b2 |
completed | April 30, 2026, 12:23 p.m. |
| NER | Named-entity recognition | batch_69f71362f1448190985a80ce7af475cb |
completed | May 3, 2026, 9:20 a.m. |
| PD | Predicate disambiguation | batch_69f7127884388190884f23d181a65d19 |
completed | May 3, 2026, 9:16 a.m. |
Created at: May 1, 2026, 1:56 a.m.