Triple
T25604835
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | St. John Bosco High School (early years) |
E641881
|
entity |
| Predicate | relatedToSport |
P67409
|
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: [St. John Bosco High School (early years), relatedToSport, basketball]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relatedToSport Context triple: [St. John Bosco High School (early years), relatedToSport, basketball]
-
A.
relatedSport
chosen
Indicates that there is an association or connection between an entity and a particular sport.
-
B.
relationshipTypeWithSport
Indicates the specific type or nature of the relationship an entity has with a particular sport (e.g., participation, affiliation, or role).
-
C.
associatedWithTeamSport
Indicates a relationship where an entity is connected to, involved in, or participates in a team-based sport.
-
D.
hasRelativeInSport
Indicates that one entity has a family member who participates or is involved in a sport-related activity or profession.
-
E.
relatedToClub
Indicates that there is an association or connection between an entity and a club, without specifying the exact nature of that relationship.
- 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_69e75dc6ccf081908d49578fd36a76d5 |
completed | April 21, 2026, 11:21 a.m. |
| NER | Named-entity recognition | batch_69fcef654d588190b29ecc76678d1aa0 |
completed | May 7, 2026, 8 p.m. |
| PD | Predicate disambiguation | batch_69fcecdb97f48190b382b7d13be92dc0 |
completed | May 7, 2026, 7:49 p.m. |
Created at: April 21, 2026, 4:37 p.m.