Triple
T3813734
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tyronn Lue |
E84198
|
entity |
| Predicate | nbaChampionshipsAsHeadCoach |
P15415
|
FINISHED |
| Object | 1 |
—
|
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: 1 | Statement: [Tyronn Lue, nbaChampionshipsAsHeadCoach, 1]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: nbaChampionshipsAsHeadCoach Context triple: [Tyronn Lue, nbaChampionshipsAsHeadCoach, 1]
-
A.
numberOfNBAChampionshipsAsHeadCoach
chosen
Indicates the count of NBA championship titles an individual has won while serving as a head coach.
-
B.
championshipWonAsCoach
Indicates that the subject, acting in the role of coach, has won a championship title with the associated team or organization.
-
C.
NBAChampionshipsAsExecutive
Indicates the number of NBA championships a person has won while serving in an executive or front-office role for a team.
-
D.
careerNBARegularSeasonWinsAsCoach
Indicates the total number of NBA regular season games a person has won in their role as a head coach.
-
E.
gamesWonAsHeadCoach
Indicates the number of games that an individual has won while serving in the role of 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_69aed931f5908190be2c07af66d4df25 |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aef1515c688190a38332aedeed8a76 |
completed | March 9, 2026, 4:12 p.m. |
| PD | Predicate disambiguation | batch_69aee7482d708190a3ec74745b102a4c |
completed | March 9, 2026, 3:29 p.m. |
Created at: March 9, 2026, 3:17 p.m.