Triple
T12180462
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | BAFTA Award for Outstanding British Film (as writer/director of Nil by Mouth) |
E290202
|
entity |
| Predicate | genreOfHonouredFilm |
P93695
|
FINISHED |
| Object | 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: drama | Statement: [BAFTA Award for Outstanding British Film (as writer/director of Nil by Mouth), genreOfHonouredFilm, drama]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: genreOfHonouredFilm Context triple: [BAFTA Award for Outstanding British Film (as writer/director of Nil by Mouth), genreOfHonouredFilm, drama]
-
A.
featuredInFilmGenre
Indicates that an entity (such as a film, character, or work) appears in or is associated with a specific film genre.
-
B.
genreOfPersonHonored
Indicates the artistic or professional genre associated with the person who is being honored.
-
C.
genreOfAwards
Indicates the type or category of awards associated with a given work, event, or entity.
-
D.
sourceFilmGenre
chosen
Indicates that a film is classified as belonging to a particular genre.
-
E.
associatedAwardWinningFilm
Indicates that there is a relationship between an entity and a film with which it is connected, where that film has received an award.
- 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_69d6ab64de5881908d56eb7a75c6cc69 |
completed | April 8, 2026, 7:24 p.m. |
| NER | Named-entity recognition | batch_69d91a83012c81908d04bbab5fdcd8c2 |
completed | April 10, 2026, 3:42 p.m. |
| PD | Predicate disambiguation | batch_69d91510a258819090ef8fbdc2d8707b |
completed | April 10, 2026, 3:19 p.m. |
Created at: April 8, 2026, 9:50 p.m.