Triple
T33502110
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Brian Backer |
E858016
|
entity |
| Predicate | hasGenreAsPerceivedActorType |
P191103
|
FINISHED |
| Object | comedy |
—
|
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 | Statement: [Brian Backer, hasGenreAsPerceivedActorType, comedy]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasGenreAsPerceivedActorType Context triple: [Brian Backer, hasGenreAsPerceivedActorType, comedy]
-
A.
hasGenreAsPerception
chosen
Indicates that something is associated with a genre specifically in terms of how it is perceived or interpreted, rather than as an objective classification.
-
B.
hasGenreInRoles
Indicates that an entity participates in roles associated with a particular genre or set of genres.
-
C.
hasGenreRelation
Indicates that there is an association between an entity and a specific genre, specifying the type or category it belongs to.
-
D.
hasGivenGenre
Indicates that an entity is associated with a specific genre that has been assigned or designated to it.
-
E.
hasGenreAsSetting
Indicates that a work’s setting is characterized by, or takes place within, a particular 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_69f3497660508190a541826a81f7e9ab |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_69fd4129a8848190a5002150278ac689 |
completed | May 8, 2026, 1:49 a.m. |
| PD | Predicate disambiguation | batch_69fd3e0515ec8190937c7af71ebc3875 |
completed | May 8, 2026, 1:36 a.m. |
Created at: May 1, 2026, 1:38 a.m.