Triple
T16785718
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dr. Traherne |
E407966
|
entity |
| Predicate | workGenreAppearsIn |
P55464
|
FINISHED |
| Object | adventure 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: adventure film | Statement: [Dr. Traherne, workGenreAppearsIn, adventure film]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: workGenreAppearsIn Context triple: [Dr. Traherne, workGenreAppearsIn, adventure film]
-
A.
genreOfWorkActedIn
Indicates that an entity is the genre category of a work in which another entity performed or acted.
-
B.
hasFilmographyType
Indicates the type or category of film-related work associated with an entity (e.g., actor, director, producer) within its filmography.
-
C.
genreOfWorkCharacterIsIn
chosen
Indicates the specific genre of the creative work in which a given character appears.
-
D.
actsIn
Indicates that an entity performs or appears in a creative work, such as a film, play, or show.
-
E.
authorOfWorkHeAppearsIn
Indicates that a person is the author of a work in which he himself appears as a character or subject.
- 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_69d8839270588190886720d9519bbf8f |
completed | April 10, 2026, 4:58 a.m. |
| NER | Named-entity recognition | batch_69e3b21a52ac8190b4374aa0fc45683a |
completed | April 18, 2026, 4:32 p.m. |
| PD | Predicate disambiguation | batch_69e319cf691c819083e39225f5777ef0 |
completed | April 18, 2026, 5:42 a.m. |
Created at: April 10, 2026, 5:22 a.m.