Triple
T15549682
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Wu Ashun |
E370708
|
entity |
| Predicate | teamOrIndividualSport |
P67409
|
FINISHED |
| Object | individual sport |
—
|
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: individual sport | Statement: [Wu Ashun, teamOrIndividualSport, individual sport]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: teamOrIndividualSport Context triple: [Wu Ashun, teamOrIndividualSport, individual sport]
-
A.
associatedWithTeamSport
Indicates a relationship where an entity is connected to, involved in, or participates in a team-based sport.
-
B.
tenantSport
Indicates that a tenant participates in or is associated with a particular sport.
-
C.
sportsAssociation
Indicates a formal relationship in which an entity is affiliated with, governed by, or participates under the auspices of a specific sports organization or governing body.
-
D.
relatedSport
chosen
Indicates that there is an association or connection between an entity and a particular sport.
-
E.
sportNumber
Indicates the specific jersey or uniform number associated with an athlete in a sporting context.
- 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_69d85cc6cf40819091f4a5facee1ebe6 |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69e04a93121881909d88ca55a39252ac |
completed | April 16, 2026, 2:33 a.m. |
| PD | Predicate disambiguation | batch_69deda7a95c48190bbe29fadcf17191a |
completed | April 15, 2026, 12:23 a.m. |
Created at: April 10, 2026, 4:08 a.m.