Triple
T442065
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Michigan Wolverines football |
E10133
|
entity |
| Predicate | nationalChampionshipsClaimed |
P6611
|
FINISHED |
| Object | multiple |
—
|
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: multiple | Statement: [Michigan Wolverines football, nationalChampionshipsClaimed, multiple]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: nationalChampionshipsClaimed Context triple: [Michigan Wolverines football, nationalChampionshipsClaimed, multiple]
-
A.
hasChampionships
Indicates that one entity possesses or has won one or more championships associated with another entity.
-
B.
hasWonNCAATitleIn
Indicates that an entity has won an NCAA championship title in a specified sport, category, or year.
-
C.
NCAAChampionship
chosen
Indicates that an entity has won, holds, or is otherwise associated with an NCAA (National Collegiate Athletic Association) championship title in a particular sport or event.
-
D.
championshipRecognition
Indicates formal acknowledgment that an entity has won or holds a championship title in a given competition or domain.
-
E.
SuperBowlChampionCount
Indicates the number of Super Bowl championships an entity (typically a team or franchise) 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_69a2e8465ef481909655c681b01e2986 |
completed | Feb. 28, 2026, 1:06 p.m. |
| NER | Named-entity recognition | batch_69a2ef42b4008190abed9d79926c7022 |
completed | Feb. 28, 2026, 1:36 p.m. |
| PD | Predicate disambiguation | batch_69a2edde2b9c8190bd20b582eb4c5065 |
completed | Feb. 28, 2026, 1:30 p.m. |
Created at: Feb. 28, 2026, 1:11 p.m.