Triple
T7425837
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 1960 NCAA Men's Division I Basketball Championship |
E171364
|
entity |
| Predicate | championTitleCountForSchool |
P25122
|
FINISHED |
| Object | 1 |
—
|
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: 1 | Statement: [1960 NCAA Men's Division I Basketball Championship, championTitleCountForSchool, 1]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: championTitleCountForSchool Context triple: [1960 NCAA Men's Division I Basketball Championship, championTitleCountForSchool, 1]
-
A.
winnerTitleCount
chosen
Indicates the number of titles or championships an entity has won.
-
B.
championPreviousTitleYear
Indicates the year in which the current champion previously held the same title.
-
C.
consecutiveTitlesForChampion
Indicates that a champion has won multiple titles in succession without interruption.
-
D.
numberOfLeagueTitles
Indicates the total count of league championship titles that an entity has won.
-
E.
collegeTeamChampionships
Indicates the championships or titles that a college sports team 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_69c68a625d048190af70eb8b63bec5a0 |
completed | March 27, 2026, 1:47 p.m. |
| NER | Named-entity recognition | batch_69c6f303eb988190ba9df7946fce1c86 |
completed | March 27, 2026, 9:13 p.m. |
| PD | Predicate disambiguation | batch_69c6f03648d08190b862d07fef71210c |
completed | March 27, 2026, 9:01 p.m. |
Created at: March 27, 2026, 3:12 p.m.