Triple
T4398492
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | NCAA men’s volleyball |
E99551
|
entity |
| Predicate | pointsToWinSet |
P55868
|
FINISHED |
| Object | 25 points (15 in deciding set) |
—
|
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: 25 points (15 in deciding set) | Statement: [NCAA men’s volleyball, pointsToWinSet, 25 points (15 in deciding set)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: pointsToWinSet Context triple: [NCAA men’s volleyball, pointsToWinSet, 25 points (15 in deciding set)]
-
A.
pointsForWin
Indicates the number of points awarded to an entity for achieving a win in a given context or competition.
-
B.
winnerPoints
Indicates the number of points earned by the winning participant or entity in a competition or event.
-
C.
numberOfWinsRequired
Indicates the specific count of wins an entity must achieve to meet a defined goal, threshold, or condition.
-
D.
numberOfWins
Indicates the count of times an entity has achieved victory in a relevant context or competition.
-
E.
gameWinningScoreBy
Indicates that a particular score is the decisive amount by which a game is won by an entity.
- 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_69b345506b408190b0e3dee616738a7d |
completed | March 12, 2026, 10:59 p.m. |
| NER | Named-entity recognition | batch_69b352adce588190b9e6ed53458aa1e1 |
completed | March 12, 2026, 11:56 p.m. |
| PD | Predicate disambiguation | batch_69b34f597998819092477efdedb51427 |
completed | March 12, 2026, 11:42 p.m. |
| PDg | Predicate description generation | batch_69b34ff654308190b9717526120d80d3 |
completed | March 12, 2026, 11:44 p.m. |
Created at: March 12, 2026, 11:20 p.m.