Triple
T17862578
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Capella International |
E446110
|
entity |
| Predicate | genreInvolved |
P21380
|
FINISHED |
| Object | comedy films |
—
|
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 films | Statement: [Capella International, genreInvolved, comedy films]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: genreInvolved Context triple: [Capella International, genreInvolved, comedy films]
-
A.
genreWithin
Indicates that one genre is a subgenre or more specific category contained within another, broader genre.
-
B.
genreIncludes
Indicates that a broader genre category encompasses or contains a specified subgenre or work as part of its classification.
-
C.
genreAssociatedWith
Indicates a relationship where a work, item, or entity is linked to or categorized under a particular genre.
-
D.
genre
Indicates the artistic or thematic category to which a work (such as a book, film, or song) belongs.
-
E.
genreSpecialty
chosen
Indicates that an entity specializes in or is particularly associated with a specific genre.
- 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_69d8b9f26f18819089c9e43250bee6ae |
completed | April 10, 2026, 8:50 a.m. |
| NER | Named-entity recognition | batch_69e49790ea148190b7a966812d44f430 |
completed | April 19, 2026, 8:51 a.m. |
| PD | Predicate disambiguation | batch_69e3d8e6d2e88190ad9ef9f8a99f13e6 |
completed | April 18, 2026, 7:17 p.m. |
Created at: April 10, 2026, 10:17 a.m.