Triple
T13257455
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kilter Films |
E315695
|
entity |
| Predicate | hasGenreInPortfolio |
P109183
|
FINISHED |
| Object | science fiction television |
—
|
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: science fiction television | Statement: [Kilter Films, hasGenreInPortfolio, science fiction television]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasGenreInPortfolio Context triple: [Kilter Films, hasGenreInPortfolio, science fiction television]
-
A.
hasGenreInRoles
Indicates that an entity participates in roles associated with a particular genre or set of genres.
-
B.
hasUseGenre
Indicates that something (such as a work, product, or item) is associated with or categorized under a particular genre for its use or purpose.
-
C.
hasGenreScope
Indicates that something (such as a work, collection, or classification) is limited to, defined by, or applicable within a particular genre or set of genres.
-
D.
hasGenreInBibliography
Indicates that a work’s bibliography includes sources belonging to a specified genre.
-
E.
hasGenreAsOutput
Indicates that an entity produces, results in, or outputs a particular genre as its outcome.
- F. None of above. chosen
Provenance (4 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_69d806b1d9ac8190852c5571d5bd5f0f |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69d99cfdc9388190af1fdd3cd4717bd8 |
completed | April 11, 2026, 12:59 a.m. |
| PD | Predicate disambiguation | batch_69d98f60911081909fa346a054f76c9f |
completed | April 11, 2026, 12:01 a.m. |
| PDg | Predicate description generation | batch_69d99cf7f9c48190a6a4f452b4a2aefa |
completed | April 11, 2026, 12:59 a.m. |
Created at: April 9, 2026, 9:25 p.m.