Triple
T18647875
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pat Dye |
E455850
|
entity |
| Predicate | overallCollegeHeadCoachingRecord |
P76762
|
FINISHED |
| Object | 153–62–5 |
—
|
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: 153–62–5 | Statement: [Pat Dye, overallCollegeHeadCoachingRecord, 153–62–5]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: overallCollegeHeadCoachingRecord Context triple: [Pat Dye, overallCollegeHeadCoachingRecord, 153–62–5]
-
A.
overallCollegeCoachingRecord
chosen
Indicates the summarized win-loss (and often tie) coaching performance record of a college coach across all seasons and teams.
-
B.
coachingRecordCollegeWins
Indicates the number of games a coach has won at the college level in their coaching record.
-
C.
playedForCollegeCoach
Indicates that an athlete was coached by a specific college coach while playing for that coach’s team.
-
D.
coachingRecordCollegeLosses
Indicates the number of games a coach’s college team has lost in their coaching record.
-
E.
collegeFootballHeadCoachAt
Indicates that a person holds the position of head coach for a specified college football team or program.
- 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_69d8d38ea1e88190997e9b231190ba6f |
completed | April 10, 2026, 10:40 a.m. |
| NER | Named-entity recognition | batch_69e5500f007c81908b1835569be913d7 |
completed | April 19, 2026, 9:58 p.m. |
| PD | Predicate disambiguation | batch_69e478d85864819093cbad5ed9b54878 |
completed | April 19, 2026, 6:40 a.m. |
Created at: April 10, 2026, 11:47 a.m.