Triple
T19840625
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | WNBA games |
E476715
|
entity |
| Predicate | foulLimitPerPlayer |
P137534
|
FINISHED |
| Object | 6 personal fouls (typical) |
—
|
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 personal fouls (typical) | Statement: [WNBA games, foulLimitPerPlayer, 6 personal fouls (typical)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: foulLimitPerPlayer Context triple: [WNBA games, foulLimitPerPlayer, 6 personal fouls (typical)]
-
A.
foulLimitPerTeam
Indicates the maximum number of fouls that a single team is allowed to commit within a defined game or competition context.
-
B.
penaltyFrom10thFoul
Indicates that a penalty situation arises as a result of a team or player committing their tenth foul.
-
C.
teamLimitPerGame
Indicates the maximum number of times a team is allowed to participate or be involved in a single game or match.
-
D.
penaltyFrom7thFoul
Indicates that a penalty situation arises as a result of committing a seventh foul.
-
E.
hasFoulType
Indicates that an entity is associated with or characterized by a specific type or category of foul (e.g., in a game, sport, or rule system).
- 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_69d8e51d39d081909bcfafeaaf3d2fcc |
completed | April 10, 2026, 11:55 a.m. |
| NER | Named-entity recognition | batch_69e6580576748190b85e234b01209ae7 |
completed | April 20, 2026, 4:44 p.m. |
| PD | Predicate disambiguation | batch_69e537e21d2881909b1be82f02b99d40 |
completed | April 19, 2026, 8:15 p.m. |
| PDg | Predicate description generation | batch_69e543c136b081909cab9394b958390a |
completed | April 19, 2026, 9:06 p.m. |
Created at: April 10, 2026, 1:51 p.m.