Triple
T461427
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tennessee Lady Volunteers basketball |
E7346
|
entity |
| Predicate | PatSummittWins |
P15068
|
FINISHED |
| Object | over 1000 career wins |
—
|
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: over 1000 career wins | Statement: [Tennessee Lady Volunteers basketball, PatSummittWins, over 1000 career wins]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: PatSummittWins Context triple: [Tennessee Lady Volunteers basketball, PatSummittWins, over 1000 career wins]
-
A.
venueOfBattleOfTheSexes
Indicates the location where the "Battle of the Sexes" event took place.
-
B.
hasWonNCAATitleIn
Indicates that an entity has won an NCAA championship title in a specified sport, category, or year.
-
C.
NCAAChampionship
Indicates that an entity has won, holds, or is otherwise associated with an NCAA (National Collegiate Athletic Association) championship title in a particular sport or event.
-
D.
firstNCAATournamentWin
Indicates the event in which an entity achieves its first-ever victory in an NCAA tournament game.
-
E.
finalsLosingTeam
Indicates the team that was defeated in the final match of a competition or tournament.
- F. None of above. chosen
Provenance (4 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_69a2e7e5c5bc8190a1dc8178218fba40 |
completed | Feb. 28, 2026, 1:04 p.m. |
| NER | Named-entity recognition | batch_69a2efbed5b88190a45716812eb4cfdf |
completed | Feb. 28, 2026, 1:38 p.m. |
| PD | Predicate disambiguation | batch_69a2ede75b6c81908350103d21f22a03 |
completed | Feb. 28, 2026, 1:30 p.m. |
| PDg | Predicate description generation | batch_69a2ef257a548190a96bfa0cf6183976 |
completed | Feb. 28, 2026, 1:35 p.m. |
Created at: Feb. 28, 2026, 1:12 p.m.