Triple
T2682554
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pat Summitt |
E57405
|
entity |
| Predicate | totalCareerLossesAsCollegeCoach |
P39703
|
FINISHED |
| Object | 208 |
—
|
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: 208 | Statement: [Pat Summitt, totalCareerLossesAsCollegeCoach, 208]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: totalCareerLossesAsCollegeCoach Context triple: [Pat Summitt, totalCareerLossesAsCollegeCoach, 208]
-
A.
coachingRecordCollegeLosses
chosen
Indicates the number of games a coach’s college team has lost in their coaching record.
-
B.
coachingRecordCollegeWins
Indicates the number of games a coach has won at the college level in their coaching record.
-
C.
collegeTeamCoached
Indicates that a person has served as a coach for a particular college sports team.
-
D.
notableAssistantCoaches
Indicates that the subject has assistant coaches who are particularly distinguished or noteworthy in their roles.
-
E.
coachingRecordCollegeTies
Indicates a relationship where a coaching record is associated with one or more colleges to which it is tied (e.g., where the coaching occurred or is attributed).
- 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_69ab4a5028388190a36f3baf1588309e |
completed | March 6, 2026, 9:42 p.m. |
| NER | Named-entity recognition | batch_69abd9d602848190b638e417e710a555 |
completed | March 7, 2026, 7:55 a.m. |
| PD | Predicate disambiguation | batch_69abd81c9b4c81908e5e0da6ac5f828b |
completed | March 7, 2026, 7:47 a.m. |
Created at: March 6, 2026, 9:54 p.m.