Triple
T25622700
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 2017 NCAA Division I men's basketball tournament |
E642342
|
entity |
| Predicate | championNCAATitleCount |
P24536
|
FINISHED |
| Object | 6 |
—
|
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: 6 | Statement: [2017 NCAA Division I men's basketball tournament, championNCAATitleCount, 6]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: championNCAATitleCount Context triple: [2017 NCAA Division I men's basketball tournament, championNCAATitleCount, 6]
-
A.
hasWonNCAATitleIn
Indicates that an entity has won an NCAA championship title in a specified sport, category, or year.
-
B.
NCAATournamentWins
Indicates the number of games a team has won in NCAA basketball tournaments.
-
C.
NCAAChampionshipCount
chosen
Indicates the number of NCAA championships an entity has won.
-
D.
firstIndividualNCAATitlesCount
Indicates the number of NCAA titles won by the first individual in the relationship.
-
E.
consecutiveNCAAChampionships
Indicates that the subject has won NCAA championships in consecutive years, with the object specifying the number of such back-to-back titles.
- 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_69e77e7a96748190b10f2699041e4e43 |
completed | April 21, 2026, 1:41 p.m. |
| NER | Named-entity recognition | batch_69f5fa2121f4819082c5135147a0f0d9 |
completed | May 2, 2026, 1:20 p.m. |
| PD | Predicate disambiguation | batch_69f4807f8680819098a524158d049c63 |
completed | May 1, 2026, 10:29 a.m. |
Created at: April 21, 2026, 5:06 p.m.