Triple
T37100300
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 2018 Big Ten Men's Basketball Tournament |
E918681
|
entity |
| Predicate | championTitleCountForMichigan |
P155255
|
FINISHED |
| Object | 2 |
—
|
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: 2 | Statement: [2018 Big Ten Men's Basketball Tournament, championTitleCountForMichigan, 2]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: championTitleCountForMichigan Context triple: [2018 Big Ten Men's Basketball Tournament, championTitleCountForMichigan, 2]
-
A.
championTitleCountFranchise
Indicates the number of championship titles a franchise has won.
-
B.
numberOfChampionTitles
chosen
Indicates the total count of championship titles that an entity has won.
-
C.
championsTitleWonBy
Indicates that a particular championship title is held or has been won by a specific entity.
-
D.
championTitleCountForCanada
Indicates the number of championship titles that have been won on behalf of Canada.
-
E.
championSeriesWins
Indicates that one entity has won a championship series a specified number of times or in a specified context relative to another entity.
- 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_69f76e9a48bc8190a3947508d8bca408 |
completed | May 3, 2026, 3:49 p.m. |
| NER | Named-entity recognition | batch_69fcf1b3d9a08190850b388308656266 |
completed | May 7, 2026, 8:10 p.m. |
| PD | Predicate disambiguation | batch_69fcf0226d8c8190b23dceafb1794995 |
completed | May 7, 2026, 8:03 p.m. |
Created at: May 3, 2026, 4:14 p.m.