Triple
T17008743
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | John du Pont |
E412641
|
entity |
| Predicate | sportsDisciplineSupported |
P126186
|
FINISHED |
| Object | freestyle wrestling |
—
|
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: freestyle wrestling | Statement: [John du Pont, sportsDisciplineSupported, freestyle wrestling]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: sportsDisciplineSupported Context triple: [John du Pont, sportsDisciplineSupported, freestyle wrestling]
-
A.
includesSport
Indicates that one entity contains, offers, or features a particular sport as part of its activities, content, or composition.
-
B.
esportDiscipline
Indicates that one entity is a specific esports game or discipline in which the other entity participates or is involved.
-
C.
hasOlympicDiscipline
Indicates that an entity (typically a sport) includes or is associated with a specific discipline as recognized in the Olympic Games.
-
D.
sportEventType
Indicates the specific kind or category of sport associated with a given sporting event.
-
E.
appliesToSports
Indicates that something is relevant, appropriate, or specifically intended for use in the context of sports.
- 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_69d886cb581c8190ab05f4b429c9cd85 |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e3d3853f548190910240a2145cc890 |
completed | April 18, 2026, 6:55 p.m. |
| PD | Predicate disambiguation | batch_69e35d552bc08190af17ef7659e094ef |
completed | April 18, 2026, 10:30 a.m. |
| PDg | Predicate description generation | batch_69e378e037c88190935d732e0f10d5d7 |
completed | April 18, 2026, 12:28 p.m. |
Created at: April 10, 2026, 5:32 a.m.