Triple
T8244258
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Man Who Loved Flowers |
E192810
|
entity |
| Predicate | partOfCollectionGenre |
P1925
|
FINISHED |
| Object | horror short story collection |
—
|
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: horror short story collection | Statement: [The Man Who Loved Flowers, partOfCollectionGenre, horror short story collection]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: partOfCollectionGenre Context triple: [The Man Who Loved Flowers, partOfCollectionGenre, horror short story collection]
-
A.
genreOfCollection
Indicates that a specified genre categorizes or characterizes a particular collection.
-
B.
partOfCollection
chosen
Indicates that an entity belongs to, or is included within, a larger collection or set.
-
C.
coveredInGenre
Indicates that a work or item is associated with, categorized under, or treated within a particular genre.
-
D.
genreWithin
Indicates that one genre is a subgenre or more specific category contained within another, broader genre.
-
E.
publishedGenre
Indicates that an entity has been published in, or is associated with, a particular genre.
- 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.