Triple
T3847526
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nini |
E85207
|
entity |
| Predicate | representsSport |
P17899
|
FINISHED |
| Object | gymnastics |
—
|
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: gymnastics | Statement: [Nini, representsSport, gymnastics]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: representsSport Context triple: [Nini, representsSport, gymnastics]
-
A.
representsInSport
chosen
Indicates that one entity serves as an official representative of another entity within the context of a particular sport or sporting domain.
-
B.
representsSportLevel
Indicates that an entity participates in or is associated with a particular level or tier within a sport.
-
C.
sponsorSport
Indicates that one entity financially or materially supports a sport or sporting activity, typically in exchange for promotion or association.
-
D.
includesSport
Indicates that one entity contains, offers, or features a particular sport as part of its activities, content, or composition.
-
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_69aed936de1c81908f91bed80f70abb2 |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aeebcb069881909d3536b18b7802a7 |
completed | March 9, 2026, 3:48 p.m. |
| PD | Predicate disambiguation | batch_69aee750377c8190af70c79768c0edd8 |
completed | March 9, 2026, 3:29 p.m. |
Created at: March 9, 2026, 3:18 p.m.