Triple
T3038216
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | John Madden |
E83061
|
entity |
| Predicate | gamesWonAsHeadCoach |
P44734
|
FINISHED |
| Object | 103 (regular season) |
—
|
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: 103 (regular season) | Statement: [John Madden, gamesWonAsHeadCoach, 103 (regular season)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: gamesWonAsHeadCoach Context triple: [John Madden, gamesWonAsHeadCoach, 103 (regular season)]
-
A.
numberOfNBAChampionshipsAsHeadCoach
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.
numberOfSuperBowlsWonAsHeadCoach
Indicates the total count of Super Bowl championships an individual has won while serving in the role of head coach.
-
D.
careerNBARegularSeasonWinsAsCoach
Indicates the total number of NBA regular season games a person has won in their role as a head coach.
-
E.
headCoachWinningTeam
Indicates that the subject is the head coach of the team that won a particular game, match, or competition.
- F. None of above. chosen
Provenance (4 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_69ad8b2298908190a7cb4e9bdbf064d0 |
completed | March 8, 2026, 2:43 p.m. |
| NER | Named-entity recognition | batch_69ad9b2e03c88190b4e2f01f07c9303a |
completed | March 8, 2026, 3:52 p.m. |
| PD | Predicate disambiguation | batch_69ad961fc62c819087c4c3a44b00847d |
completed | March 8, 2026, 3:30 p.m. |
| PDg | Predicate description generation | batch_69ad97f6af3881909f4547967384114c |
completed | March 8, 2026, 3:38 p.m. |
Created at: March 8, 2026, 3:01 p.m.