Triple
T2678039
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bo Schembechler |
E56505
|
entity |
| Predicate | conferenceChampionshipsWon |
P313
|
FINISHED |
| Object | 13 Big Ten Conference titles |
—
|
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: 13 Big Ten Conference titles | Statement: [Bo Schembechler, conferenceChampionshipsWon, 13 Big Ten Conference titles]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: conferenceChampionshipsWon Context triple: [Bo Schembechler, conferenceChampionshipsWon, 13 Big Ten Conference titles]
-
A.
hasChampionships
chosen
Indicates that one entity possesses or has won one or more championships associated with another entity.
-
B.
majorChampionshipWins
Indicates the number of major championship titles an entity has won.
-
C.
conferenceChampionshipAppearancesThrough2023
Indicates the number of times an entity has appeared in conference championship games or series up to and including the 2023 season.
-
D.
teamWonChampionship
Indicates that a particular team has secured victory in a championship competition.
-
E.
leagueChampionships
Indicates the number of league championship titles an entity has won.
- 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_69ab4a4b13fc81909dfdb3f23da46832 |
completed | March 6, 2026, 9:42 p.m. |
| NER | Named-entity recognition | batch_69abda2f7bf88190a1e3103dd014d871 |
completed | March 7, 2026, 7:56 a.m. |
| PD | Predicate disambiguation | batch_69abd81ab9d08190b72b6104c6dbc769 |
completed | March 7, 2026, 7:47 a.m. |
Created at: March 6, 2026, 9:54 p.m.