Triple
T33184792
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Alan Brady |
E849435
|
entity |
| Predicate | hasGenreInUniverse |
P164301
|
FINISHED |
| Object | variety show |
—
|
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: variety show | Statement: [Alan Brady, hasGenreInUniverse, variety show]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasGenreInUniverse Context triple: [Alan Brady, hasGenreInUniverse, variety show]
-
A.
hasFictionalUniverseGenre
Indicates that a fictional universe is associated with a particular genre that characterizes its overall style, themes, or narrative type.
-
B.
inUniverseGenre
chosen
Indicates that a work’s genre classification exists within the fictional universe itself (e.g., as an in-story show, book, or media type), rather than being an external, real-world genre label.
-
C.
hasGenreInSeries
Indicates that a particular genre is associated with, or applies to, a work as it appears within a specific series.
-
D.
hasGenreRelation
Indicates that there is an association between an entity and a specific genre, specifying the type or category it belongs to.
-
E.
hasGenreInRoles
Indicates that an entity participates in roles associated with a particular genre or set of genres.
- 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_69f3495e0f108190a6a7006f79f9c2c3 |
completed | April 30, 2026, 12:21 p.m. |
| NER | Named-entity recognition | batch_69fd32848ea88190a71e6df402bbb30e |
completed | May 8, 2026, 12:47 a.m. |
| PD | Predicate disambiguation | batch_69fd2d7e95588190991d5f21e25155df |
completed | May 8, 2026, 12:25 a.m. |
Created at: May 1, 2026, 1:29 a.m.