Triple
T12769776
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Parfumerie |
E305214
|
entity |
| Predicate | hasNotableAdaptationMedium |
P56729
|
FINISHED |
| Object | cinema |
—
|
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: cinema | Statement: [Parfumerie, hasNotableAdaptationMedium, cinema]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNotableAdaptationMedium Context triple: [Parfumerie, hasNotableAdaptationMedium, cinema]
-
A.
hasNotableAdaptationBy
Indicates that an original work has a significant adaptation created by the specified adapting entity (such as a person, group, or organization).
-
B.
notableAdaptationType
chosen
Indicates that one work is a significant adaptation of another work in a specific way or medium (e.g., film adaptation, stage adaptation).
-
C.
notableAdaptation
Indicates that one work is a significant adaptation or reinterpretation of another work.
-
D.
hasNotableAdaptationComposer
Indicates that an entity has a composer specifically responsible for the music of a notable adaptation of that entity.
-
E.
mediumAdaptation
Indicates that one work has been adapted into another form or medium (e.g., book to film, comic to TV series).
- 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_69d7bdf2b43c819098ae5aa68e61ea58 |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d96df4b36c81909bcc913dd5e535f8 |
completed | April 10, 2026, 9:39 p.m. |
| PD | Predicate disambiguation | batch_69d96409739881909174ba005a986cb5 |
completed | April 10, 2026, 8:56 p.m. |
Created at: April 9, 2026, 5:28 p.m.