Triple
T26520988
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Utah Utes track and field |
E669948
|
entity |
| Predicate | hasStudentAthletesStatus |
P22493
|
FINISHED |
| Object | amateur |
—
|
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: amateur | Statement: [Utah Utes track and field, hasStudentAthletesStatus, amateur]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasStudentAthletesStatus Context triple: [Utah Utes track and field, hasStudentAthletesStatus, amateur]
-
A.
hasNumberOfStudentAthletes
Indicates the relationship that specifies how many student athletes are associated with a given entity.
-
B.
hasScholarshipAthletes
Indicates that an institution or team includes athletes who are receiving scholarships.
-
C.
hasSportsStatus
chosen
Indicates that an entity holds a particular sports-related status, role, or classification (such as amateur, professional, active, or retired) within a sporting context.
-
D.
hasAthleticProgramType
Indicates that an institution’s athletic program belongs to or is classified under a specific type or category of athletic program.
-
E.
hasStudentEnrollment
Indicates that a person or entity is enrolled as a student in a particular course, program, or educational institution.
- 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_69eeb31b6dcc8190b30632dc3928a0c0 |
completed | April 27, 2026, 12:51 a.m. |
| NER | Named-entity recognition | batch_69f7465687bc8190a9da44d62b634ed7 |
completed | May 3, 2026, 12:57 p.m. |
| PD | Predicate disambiguation | batch_69f743f4ceb08190a21fe7f4a99b166b |
completed | May 3, 2026, 12:47 p.m. |
Created at: April 27, 2026, 1:27 a.m.