Triple
T13608692
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tucker-Pritchett family |
E325130
|
entity |
| Predicate | showGenreContext |
P20075
|
FINISHED |
| Object | sitcom |
—
|
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: sitcom | Statement: [Tucker-Pritchett family, showGenreContext, sitcom]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: showGenreContext Context triple: [Tucker-Pritchett family, showGenreContext, sitcom]
-
A.
targetGenre
Indicates the genre that something is specifically aimed at, categorized under, or intended to belong to.
-
B.
gameGenreContext
Indicates the genre or type of game associated with a given game entity or gaming context.
-
C.
coveredInGenre
Indicates that a work or item is associated with, categorized under, or treated within a particular genre.
-
D.
genreContext
chosen
Indicates the contextual genre or categorical style associated with an entity, such as the thematic or stylistic framework in which it is situated.
-
E.
genreOfAppearance
Indicates the genre or type of creative work in which an entity appears.
- 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_69d80769eaf081909d82f44e484d6113 |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69dbbb9ee3f081909056dc1a92c40b7a |
completed | April 12, 2026, 3:34 p.m. |
| PD | Predicate disambiguation | batch_69dbae1b3ee481909bd43ded6227a3e5 |
completed | April 12, 2026, 2:37 p.m. |
Created at: April 9, 2026, 9:50 p.m.