Triple
T33380384
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Brent Metcalf |
E854756
|
entity |
| Predicate | numberOfNCAAChampionships |
P24536
|
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: [Brent Metcalf, numberOfNCAAChampionships, multiple]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfNCAAChampionships Context triple: [Brent Metcalf, numberOfNCAAChampionships, multiple]
-
A.
NCAAChampionshipCount
chosen
Indicates the number of NCAA championships an entity has won.
-
B.
numberOfNationalChampionships
Indicates the total count of national championship titles an entity has won.
-
C.
consecutiveNCAAChampionships
Indicates that the subject has won NCAA championships in consecutive years, with the object specifying the number of such back-to-back titles.
-
D.
NCAATournamentWins
Indicates the number of games a team has won in NCAA basketball tournaments.
-
E.
wonNCAANationalChampionshipWith
Indicates that an entity secured an NCAA national championship title while being associated with or part of a specified team, school, or organization.
- 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_69f3496ca10c8190908640d18fa00832 |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_6a0314e613f88190b5dbf89b9c4203c6 |
completed | May 12, 2026, 11:54 a.m. |
| PD | Predicate disambiguation | batch_6a0314699c1c8190b2a80dc4015e7890 |
completed | May 12, 2026, 11:52 a.m. |
Created at: May 1, 2026, 1:35 a.m.