Triple
T11338093
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pine District Pictures |
E268522
|
entity |
| Predicate | notableGenreOfNotableWork |
P12590
|
FINISHED |
| Object | drama-comedy (Frances Ha) |
—
|
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-comedy (Frances Ha) | Statement: [Pine District Pictures, notableGenreOfNotableWork, drama-comedy (Frances Ha)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: notableGenreOfNotableWork Context triple: [Pine District Pictures, notableGenreOfNotableWork, drama-comedy (Frances Ha)]
-
A.
notableWorkGenre
chosen
Indicates that a particular work is recognized as notable for an entity and specifies the genre to which that work belongs.
-
B.
seriesGenreOfNotableWork
Indicates that a particular genre characterizes the notable work associated with a series.
-
C.
notableTypeOfWork
Indicates that a work is a significant or defining example within a particular type or category of work associated with an entity.
-
D.
genreOfProducedWorks
Indicates that one entity is the genre category to which the works produced by another entity belong.
-
E.
genreOfOriginWork
Indicates that a work is classified under a particular genre based on the genre of its original source work.
- 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_69d6aacb1f0881908c84a349fd1be047 |
completed | April 8, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69d7ea008b5081908e6c6c6fc29ef936 |
completed | April 9, 2026, 6:03 p.m. |
| PD | Predicate disambiguation | batch_69d787afe5a48190b8af1a3e19529641 |
completed | April 9, 2026, 11:04 a.m. |
Created at: April 8, 2026, 9:33 p.m.