Triple
T10219281
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jason Terry |
E242529
|
entity |
| Predicate | threePointSpecialist |
P31359
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Jason Terry, threePointSpecialist, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: threePointSpecialist Context triple: [Jason Terry, threePointSpecialist, true]
-
A.
threePointPercentageLeader
Indicates that the subject holds the highest three-point field goal percentage within a specified group or competition.
-
B.
threePointShooterReputation
chosen
Indicates that an entity is regarded as having notable skill or effectiveness in making three-point shots.
-
C.
usedThreePointLine
Indicates that an action or play involved or was executed from beyond the three-point line.
-
D.
careerThreePointPercentage
Indicates the proportion of three-point shots a player has successfully made over the entire span of their career.
-
E.
threePointLine
Indicates the boundary line beyond which a successful field goal attempt is scored as three points instead of two.
- F. None of above.
Provenance (3 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_69d381ae26c48190985abd0e25ee5d04 |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d3aa715a3c8190a9ccee7bcece0346 |
completed | April 6, 2026, 12:43 p.m. |
| PD | Predicate disambiguation | batch_69d3955f61f88190b8d37ff645cd44d3 |
completed | April 6, 2026, 11:13 a.m. |
Created at: April 6, 2026, 11:08 a.m.