Triple
T11393277
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lapin Agile cabaret |
E269900
|
entity |
| Predicate | hasTypicalGenre |
P55821
|
FINISHED |
| Object | chanson |
—
|
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: chanson | Statement: [Lapin Agile cabaret, hasTypicalGenre, chanson]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTypicalGenre Context triple: [Lapin Agile cabaret, hasTypicalGenre, chanson]
-
A.
typicalGenresIncluded
chosen
Indicates that certain genres are commonly or characteristically included as part of another entity’s usual set of genres.
-
B.
hasNotableGenre
Indicates that an entity is significantly associated with a particular genre, such that the genre is especially characteristic or noteworthy for that entity.
-
C.
hasMainGenre
Indicates that an entity’s primary or most characteristic genre is the specified genre.
-
D.
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.
-
E.
hasGenreOfClaim
Indicates that a claim is categorized or classified under a particular genre or type of claim.
- 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_69d6aacdbc6c8190af6dc3d5f5d22836 |
completed | April 8, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69d8001796f48190822526f52e3f0337 |
completed | April 9, 2026, 7:37 p.m. |
| PD | Predicate disambiguation | batch_69d7e70b228c8190b87f5101fd683788 |
completed | April 9, 2026, 5:51 p.m. |
Created at: April 8, 2026, 9:34 p.m.