Triple
T3599571
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Steve Nash |
E76221
|
entity |
| Predicate | careerThreePointPercentage |
P50140
|
FINISHED |
| Object | .428 |
—
|
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: .428 | Statement: [Steve Nash, careerThreePointPercentage, .428]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: careerThreePointPercentage Context triple: [Steve Nash, careerThreePointPercentage, .428]
-
A.
MVPThreePointersAttempted
Indicates the number of three-point shots attempted by the MVP in a given context or period.
-
B.
NBAThreePointContestTitles
Indicates the number of NBA Three-Point Contest championship titles an entity has won.
-
C.
threePointShooterReputation
Indicates that an entity is regarded as having notable skill or effectiveness in making three-point shots.
-
D.
MVPThreePointersMade
Indicates the number of three-point field goals successfully made by the MVP in a game or season.
-
E.
careerPointsPerGame
Indicates the average number of points an individual scores per game over the course of their entire career.
- 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_69ad85d93dcc819094fba90cf70f4996 |
completed | March 8, 2026, 2:21 p.m. |
| NER | Named-entity recognition | batch_69adc19fd57481908ce5c9daf168e213 |
completed | March 8, 2026, 6:36 p.m. |
| PD | Predicate disambiguation | batch_69adb83b66708190bb9d2f23d6fd308e |
completed | March 8, 2026, 5:56 p.m. |
| PDg | Predicate description generation | batch_69adb9261a948190b67f6c6ac0dae2e9 |
completed | March 8, 2026, 6 p.m. |
Created at: March 8, 2026, 3:22 p.m.