Triple
T26038467
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Canaan, Tobago, Trinidad and Tobago |
E647617
|
entity |
| Predicate | hasAssociatedSportFigure |
P163862
|
FINISHED |
| Object | Dwight Yorke |
—
|
NE NERFINISHED |
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: Dwight Yorke | Statement: [Canaan, Tobago, Trinidad and Tobago, hasAssociatedSportFigure, Dwight Yorke]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasAssociatedSportFigure Context triple: [Canaan, Tobago, Trinidad and Tobago, hasAssociatedSportFigure, Dwight Yorke]
-
A.
hasAthlete
Indicates a relationship where an entity (such as a team, organization, or event) includes or is associated with one or more athletes.
-
B.
hasNameInSport
Indicates that an entity is known by a particular name specifically within the context of a given sport.
-
C.
hasPartnerInSport
Indicates that one entity has another entity as a partner with whom they jointly participate in a sport or sporting activity.
-
D.
associatedWithTeamSport
Indicates a relationship where an entity is connected to, involved in, or participates in a team-based sport.
-
E.
hasSportsRole
Indicates that an entity holds or is assigned a specific role or position within a sports context or organization.
- 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_69e77e8c88f08190858c4c81bd2e1b9a |
completed | April 21, 2026, 1:41 p.m. |
| NER | Named-entity recognition | batch_69f6416fbf4081909b0913c337927fc4 |
completed | May 2, 2026, 6:24 p.m. |
| PD | Predicate disambiguation | batch_69f63c6456608190b94e7c2e2c2a4824 |
completed | May 2, 2026, 6:03 p.m. |
| PDg | Predicate description generation | batch_69f63fd4f7448190930c723ba7cfce62 |
completed | May 2, 2026, 6:17 p.m. |
Created at: April 22, 2026, 9:08 a.m.