Triple
T8294818
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Curly Lambeau |
E194187
|
entity |
| Predicate | numberOfNFLChampionshipsWonAsCoach |
P59861
|
FINISHED |
| Object | 6 |
—
|
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: 6 | Statement: [Curly Lambeau, numberOfNFLChampionshipsWonAsCoach, 6]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfNFLChampionshipsWonAsCoach Context triple: [Curly Lambeau, numberOfNFLChampionshipsWonAsCoach, 6]
-
A.
numberOfSuperBowlsWonAsHeadCoach
Indicates the total count of Super Bowl championships an individual has won while serving in the role of head coach.
-
B.
totalNFLChampionshipsAsHeadCoach
chosen
Indicates the number of NFL championships an individual has won while serving as a head coach.
-
C.
nationalChampionshipsWonAsCoach
Indicates the number of national championship titles an individual has won specifically in the role of a coach.
-
D.
numberOfSuperBowlsWonAsAssistantCoach
Indicates the total count of Super Bowls that an individual has won specifically while serving in the role of an assistant coach.
-
E.
wonSuperBowlAsHeadCoachWith
Indicates that one entity served as the head coach of a team that won the Super Bowl with the other entity (the team) during that championship season.
- 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_69ca82e50ebc81909aa7b260c76bd757 |
completed | March 30, 2026, 2:04 p.m. |
| NER | Named-entity recognition | batch_69cb7df5fff88190ac51a8d1c3eb2fe2 |
completed | March 31, 2026, 7:55 a.m. |
| PD | Predicate disambiguation | batch_69cb70b5b5348190b296e0ecec95de60 |
completed | March 31, 2026, 6:59 a.m. |
Created at: March 30, 2026, 5:52 p.m.