Triple
T18086169
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | John Malcolm |
E432838
|
entity |
| Predicate | featuredInFilmType |
P96255
|
FINISHED |
| Object | British 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: British drama film | Statement: [John Malcolm, featuredInFilmType, British drama film]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: featuredInFilmType Context triple: [John Malcolm, featuredInFilmType, British drama film]
-
A.
featuredInFilmGenre
chosen
Indicates that an entity (such as a film, character, or work) appears in or is associated with a specific film genre.
-
B.
filmAppearanceType
Indicates the type or nature of a subject’s appearance in a film, such as a role, cameo, or other participation category.
-
C.
producedFilmType
Indicates that an entity (such as a person or organization) was responsible for producing a film of a specified type or category.
-
D.
portrayedInFilmMedium
Indicates that an entity is depicted or represented within a film or cinematic work.
-
E.
filmType
Indicates the specific category or genre that a film belongs to.
- 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_69d8b907d05c819083cc3bd6021089e6 |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e4dd150ab88190864be2a722d214b8 |
completed | April 19, 2026, 1:48 p.m. |
| PD | Predicate disambiguation | batch_69e4330e1f2881908b2506d47c48736b |
completed | April 19, 2026, 1:42 a.m. |
Created at: April 10, 2026, 10:27 a.m.