Triple
T24195797
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | LaVell Edwards |
E599831
|
entity |
| Predicate | numberOfTiesAsHeadCoach |
P44735
|
FINISHED |
| Object | 3 |
—
|
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: 3 | Statement: [LaVell Edwards, numberOfTiesAsHeadCoach, 3]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfTiesAsHeadCoach Context triple: [LaVell Edwards, numberOfTiesAsHeadCoach, 3]
-
A.
gamesTiedAsHeadCoach
chosen
Indicates that the subject and object have the same number of games that they have coached which ended in a tie, in their roles as head coaches.
-
B.
gamesWonAsHeadCoach
Indicates the number of games that an individual has won while serving in the role of head coach.
-
C.
championshipWonAsCoach
Indicates that the subject, acting in the role of coach, has won a championship title with the associated team or organization.
-
D.
headCoachTitleCount
Indicates the number of titles or championships a person has won while serving as a head coach.
-
E.
numberOfNBAChampionshipsAsHeadCoach
Indicates the count of NBA championship titles an individual has won while serving as a head coach.
- 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_69e288ceaab88190899d0acb5931591d |
completed | April 17, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69f1e24ad83c819084ac9e34d2cc2120 |
completed | April 29, 2026, 10:49 a.m. |
| PD | Predicate disambiguation | batch_69f1c43e55688190b55fc20274ed471c |
completed | April 29, 2026, 8:41 a.m. |
Created at: April 17, 2026, 11:36 p.m.