Triple
T8243827
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Boogeyman |
E192799
|
entity |
| Predicate | includedInGenreCategory |
P33225
|
FINISHED |
| Object | American horror short stories |
—
|
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: American horror short stories | Statement: [The Boogeyman, includedInGenreCategory, American horror short stories]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: includedInGenreCategory Context triple: [The Boogeyman, includedInGenreCategory, American horror short stories]
-
A.
coveredInGenre
chosen
Indicates that a work or item is associated with, categorized under, or treated within a particular genre.
-
B.
hasGenreInRoles
Indicates that an entity participates in roles associated with a particular genre or set of genres.
-
C.
hasGenreInSeries
Indicates that a particular genre is associated with, or applies to, a work as it appears within a specific series.
-
D.
containsGenreElement
Indicates that something includes or incorporates an element characteristic of a particular genre.
-
E.
typicalGenresIncluded
Indicates that certain genres are commonly or characteristically included as part of another entity’s usual 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_69ca82de7b8c81908d8106f8a53cff9b |
completed | March 30, 2026, 2:04 p.m. |
| NER | Named-entity recognition | batch_69cb78711f5081909c2f357334491a07 |
completed | March 31, 2026, 7:32 a.m. |
| PD | Predicate disambiguation | batch_69cb36b437e881909958591357e83b9d |
completed | March 31, 2026, 2:51 a.m. |
Created at: March 30, 2026, 5:47 p.m.