Triple
T19997015
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Virginia Cavaliers men's tennis |
E494218
|
entity |
| Predicate | hasNCAATeamTitles |
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: [Virginia Cavaliers men's tennis, hasNCAATeamTitles, multiple]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNCAATeamTitles Context triple: [Virginia Cavaliers men's tennis, hasNCAATeamTitles, multiple]
-
A.
hasWonNCAATitleIn
Indicates that an entity has won an NCAA championship title in a specified sport, category, or year.
-
B.
hasMostNCAAWrestlingTeamTitles
Indicates that the subject holds the highest number of NCAA wrestling team championship titles compared to all other entities.
-
C.
NCAAChampionshipCount
chosen
Indicates the number of NCAA championships an entity has won.
-
D.
hasWonNCAATitleCountBaseball
Indicates the number of NCAA baseball championship titles an entity has won.
-
E.
numberOfNationalChampionships
Indicates the total count of national championship titles an entity 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_69da626b2d748190886981ea90c8b2ea |
completed | April 11, 2026, 3:02 p.m. |
| NER | Named-entity recognition | batch_69e65fe549108190947a4d1a587c08f8 |
completed | April 20, 2026, 5:18 p.m. |
| PD | Predicate disambiguation | batch_69e537fd311881908448f2aea8b4812e |
completed | April 19, 2026, 8:15 p.m. |
Created at: April 11, 2026, 3:32 p.m.