Triple
T25582952
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Thad Matta |
E641301
|
entity |
| Predicate | tournamentTitlesWon |
P156959
|
FINISHED |
| Object | Big Ten tournament championships with Ohio State |
—
|
NE NERFINISHED |
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: Big Ten tournament championships with Ohio State | Statement: [Thad Matta, tournamentTitlesWon, Big Ten tournament championships with Ohio State]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: tournamentTitlesWon Context triple: [Thad Matta, tournamentTitlesWon, Big Ten tournament championships with Ohio State]
-
A.
majorTitleWon
Indicates that an entity has won a significant or top-level title, championship, or major award in a given domain.
-
B.
winnerTitleCount
Indicates the number of titles or championships an entity has won.
-
C.
championsTitleWonBy
chosen
Indicates that a particular championship title is held or has been won by a specific entity.
-
D.
cupSeriesTitles
Indicates the number of championship titles an entity has won in a particular cup series.
-
E.
continentalTitleWon
Indicates that an entity has won a championship or title at the continental (inter-continental or confederation-level) competition.
- 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_69e75dc42b588190a98b58e0df359674 |
completed | April 21, 2026, 11:21 a.m. |
| NER | Named-entity recognition | batch_69f621fcea1481909b6f8b3af1ee6820 |
completed | May 2, 2026, 4:10 p.m. |
| PD | Predicate disambiguation | batch_69f620dc38088190b56b2b15ed75b3c2 |
completed | May 2, 2026, 4:05 p.m. |
Created at: April 21, 2026, 4:13 p.m.