Triple
T7275315
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gene Keady |
E163010
|
entity |
| Predicate | playedSportAtCollege |
P27011
|
FINISHED |
| Object | football |
—
|
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: football | Statement: [Gene Keady, playedSportAtCollege, football]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: playedSportAtCollege Context triple: [Gene Keady, playedSportAtCollege, football]
-
A.
playedCollegeSport
chosen
Indicates that the subject participated in an organized college-level sport for the object institution.
-
B.
playedForCollegeTeamFrom
Indicates that an individual was a member of and played for a specific college team starting in a given year.
-
C.
playedCollegeTeam
Indicates that an athlete was a member of and competed for a particular college sports team.
-
D.
conferencePlayedInCollege
Indicates that a person participated in collegiate athletics within a specific athletic conference.
-
E.
positionPlayedInCollege
Indicates the specific playing position an individual held on a sports team during their college career.
- 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_69c6885c5964819085b209701769877f |
completed | March 27, 2026, 1:38 p.m. |
| NER | Named-entity recognition | batch_69c6eb8a0b4881908ff27c5a75bd4a95 |
completed | March 27, 2026, 8:41 p.m. |
| PD | Predicate disambiguation | batch_69c6e76a84a081908d4184c55b728e48 |
completed | March 27, 2026, 8:24 p.m. |
Created at: March 27, 2026, 2:58 p.m.