Triple
T11769568
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Beatrice Page |
E279861
|
entity |
| Predicate | characterInFilmGenre |
P55464
|
FINISHED |
| Object | comedy-drama film |
—
|
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 film | Statement: [Beatrice Page, characterInFilmGenre, comedy-drama film]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: characterInFilmGenre Context triple: [Beatrice Page, characterInFilmGenre, comedy-drama film]
-
A.
portraysCharacterInGenre
Indicates that an entity depicts or plays a character within works belonging to a specified genre.
-
B.
genreOfWorkActedIn
Indicates that an entity is the genre category of a work in which another entity performed or acted.
-
C.
genreOfWorkCharacterIsIn
chosen
Indicates the specific genre of the creative work in which a given character appears.
-
D.
roleInFilmEcosystem
Indicates the specific function or position an entity holds within the broader network of activities, stakeholders, and processes that make up the film ecosystem.
-
E.
givenNameInFilm
Indicates that a person is referred to by a particular given (first) name within the context of a specific film.
- 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_69d6ab01d2688190ad8ed6bda487eaa5 |
completed | April 8, 2026, 7:22 p.m. |
| NER | Named-entity recognition | batch_69d8a8c2e8b08190a31b1e284fca2aee |
completed | April 10, 2026, 7:37 a.m. |
| PD | Predicate disambiguation | batch_69d8a242cd8c819086ed6c5f292dc8cb |
completed | April 10, 2026, 7:09 a.m. |
Created at: April 8, 2026, 9:41 p.m.