Triple
T13630399
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Glove |
E325697
|
entity |
| Predicate | sportOfPersonReferredTo |
P1080
|
FINISHED |
| Object | basketball |
—
|
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: basketball | Statement: [The Glove, sportOfPersonReferredTo, basketball]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: sportOfPersonReferredTo Context triple: [The Glove, sportOfPersonReferredTo, basketball]
-
A.
knownForSports
Indicates that an entity is recognized or notable for its involvement, achievement, or association with sports.
-
B.
sportsName
Indicates the specific sport associated with or played in a given context or event.
-
C.
relatedSport
Indicates that there is an association or connection between an entity and a particular sport.
-
D.
primarySport
chosen
Indicates the main sport with which an entity (such as a person, team, or organization) is most closely associated or primarily involved.
-
E.
basedInSport
Indicates that an entity (such as a team, organization, or person) is primarily associated with or operates within a particular sport.
- 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_69d8076beddc8190a53156f5bea77f5e |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69dbc60635d08190899806fe8936f02a |
completed | April 12, 2026, 4:19 p.m. |
| PD | Predicate disambiguation | batch_69dbbe85e1c4819095194f4b7f9f6118 |
completed | April 12, 2026, 3:47 p.m. |
Created at: April 9, 2026, 9:51 p.m.