Triple
T15063789
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cameron’s Closet |
E379702
|
entity |
| Predicate | hasHorrorSubgenre |
P117175
|
FINISHED |
| Object | occult horror |
—
|
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: occult horror | Statement: [Cameron’s Closet, hasHorrorSubgenre, occult horror]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasHorrorSubgenre Context triple: [Cameron’s Closet, hasHorrorSubgenre, occult horror]
-
A.
hasHorrorElements
Indicates that something contains features, themes, or stylistic aspects characteristic of the horror genre.
-
B.
hasNotableSubgenre
Indicates that one genre is recognized as a particularly significant or prominent subgenre of another genre.
-
C.
hasCultFilmStatus
Indicates that a film has achieved cult status, typically through a dedicated, passionate fanbase despite limited or non-mainstream popularity.
-
D.
hasNotableGenre
Indicates that an entity is significantly associated with a particular genre, such that the genre is especially characteristic or noteworthy for that entity.
-
E.
hasGenreInSeries
Indicates that a particular genre is associated with, or applies to, a work as it appears within a specific series.
- 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_69d85cd7683881908d405c1b5d7b4f7f |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69dedee803ac81908bb7d66e49c2eb72 |
completed | April 15, 2026, 12:42 a.m. |
| PD | Predicate disambiguation | batch_69deb95a182081908fffc4402b02a394 |
completed | April 14, 2026, 10:02 p.m. |
| PDg | Predicate description generation | batch_69dec71e8dcc81908badc834b6ccf273 |
completed | April 14, 2026, 11 p.m. |
Created at: April 10, 2026, 3:02 a.m.