Triple
T8270097
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Réseau des sports |
E193404
|
entity |
| Predicate | targetGenre |
P82410
|
FINISHED |
| Object | professional sports |
—
|
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: professional sports | Statement: [Réseau des sports, targetGenre, professional sports]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: targetGenre Context triple: [Réseau des sports, targetGenre, professional sports]
-
A.
genreWithin
Indicates that one genre is a subgenre or more specific category contained within another, broader genre.
-
B.
commonGenre
Indicates that two entities share at least one genre in common.
-
C.
supportedGenre
Indicates that an entity (such as a system, service, or tool) is capable of handling, providing, or working with a specified genre.
-
D.
keyGenreFilm
Indicates that a particular genre is the primary or defining genre associated with a given film.
-
E.
promotesGenre
Indicates that one entity actively supports, advertises, or increases the visibility of a particular genre.
- 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_69ca82e14ae481908ffdb822cd2192bc |
completed | March 30, 2026, 2:04 p.m. |
| NER | Named-entity recognition | batch_69cb795243fc8190a66afef7476e1147 |
completed | March 31, 2026, 7:35 a.m. |
| PD | Predicate disambiguation | batch_69cb70a4525481909399d313a6247ace |
completed | March 31, 2026, 6:58 a.m. |
| PDg | Predicate description generation | batch_69cb76d648988190ab0669cc0592e827 |
completed | March 31, 2026, 7:25 a.m. |
Created at: March 30, 2026, 5:50 p.m.