Triple
T13801849
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | NBA 50–40–90 club |
E331660
|
entity |
| Predicate | threePointPercentageMinimum |
P111523
|
FINISHED |
| Object | 0.400 |
—
|
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: 0.400 | Statement: [NBA 50–40–90 club, threePointPercentageMinimum, 0.400]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: threePointPercentageMinimum Context triple: [NBA 50–40–90 club, threePointPercentageMinimum, 0.400]
-
A.
criterionFreeThrowPercentageMinimum
Indicates that a minimum free throw percentage threshold is specified as a criterion for selection or evaluation.
-
B.
criterionFieldGoalPercentageMinimum
Indicates that there is a specified minimum acceptable value for a field goal percentage used as a selection or filtering criterion.
-
C.
threePointPercentageLeader
Indicates that the subject holds the highest three-point field goal percentage within a specified group or competition.
-
D.
careerThreePointPercentage
Indicates the proportion of three-point shots a player has successfully made over the entire span of their career.
-
E.
MVPThreePointersAttempted
Indicates the number of three-point shots attempted by the MVP in a given context or period.
- 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_69d81c59f8808190a851bc56afdc55e9 |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de025ded6c8190851c108ae559a355 |
completed | April 14, 2026, 9:01 a.m. |
| PD | Predicate disambiguation | batch_69dbc85fb600819098a2aab48169be96 |
completed | April 12, 2026, 4:29 p.m. |
| PDg | Predicate description generation | batch_69dcad0eea9881908f71e1eed9a2446b |
completed | April 13, 2026, 8:45 a.m. |
Created at: April 9, 2026, 10:12 p.m.