Triple
T3657629
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Le Blaireau |
E77570
|
entity |
| Predicate | sportDisciplineOfPersonReferredTo |
P33092
|
FINISHED |
| Object | stage racing |
—
|
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: stage racing | Statement: [Le Blaireau, sportDisciplineOfPersonReferredTo, stage racing]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: sportDisciplineOfPersonReferredTo Context triple: [Le Blaireau, sportDisciplineOfPersonReferredTo, stage racing]
-
A.
sportsName
Indicates the specific sport associated with or played in a given context or event.
-
B.
typeOfAthlete
chosen
Indicates that one entity is an athlete and the other specifies the kind or category of athlete they are.
-
C.
esportDiscipline
Indicates that one entity is a specific esports game or discipline in which the other entity participates or is involved.
-
D.
sportGender
Indicates that a sport or sporting event is associated with a particular gender category (e.g., men's, women's, mixed).
-
E.
sportEventType
Indicates the specific kind or category of sport associated with a given sporting event.
- 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_69ad85def5cc8190863dccf55a18bebb |
completed | March 8, 2026, 2:21 p.m. |
| NER | Named-entity recognition | batch_69adc3d36c1c8190920397a75de4c47d |
completed | March 8, 2026, 6:45 p.m. |
| PD | Predicate disambiguation | batch_69adb84650148190bf79231105e58d7f |
completed | March 8, 2026, 5:56 p.m. |
Created at: March 8, 2026, 3:24 p.m.