Triple
T27995397
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Steve Bono |
E706997
|
entity |
| Predicate | playedCollegeFootballIn |
P109980
|
FINISHED |
| Object | NCAA Division I-A |
—
|
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: NCAA Division I-A | Statement: [Steve Bono, playedCollegeFootballIn, NCAA Division I-A]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: playedCollegeFootballIn Context triple: [Steve Bono, playedCollegeFootballIn, NCAA Division I-A]
-
A.
playedCollegeFootballInConference
Indicates that a person played college football for a team that competed within a specified athletic conference.
-
B.
playedHighSchoolFootballAt
Indicates that a person was a member of and participated in a high school football team at a specific school.
-
C.
playedCollegeSport
Indicates that the subject participated in an organized college-level sport for the object institution.
-
D.
playedForCollegeTeamFrom
Indicates that an individual was a member of and played for a specific college team starting in a given year.
-
E.
playedAmericanFootball
chosen
Indicates that one entity participated in playing American football, either professionally, collegiately, or at another organized level, during some period of time.
- 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_69ef96b980d88190a753b2f9a978595a |
completed | April 27, 2026, 5:02 p.m. |
| NER | Named-entity recognition | batch_69f6df450014819099d118e5c2d697fa |
completed | May 3, 2026, 5:38 a.m. |
| PD | Predicate disambiguation | batch_69f6de07836481908785cde9c511920b |
completed | May 3, 2026, 5:32 a.m. |
Created at: April 27, 2026, 7:53 p.m.