Triple
T1366507
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Paul Pierce |
E30013
|
entity |
| Predicate | scoredOverPoints |
P10050
|
FINISHED |
| Object | 26000 |
—
|
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: 26000 | Statement: [Paul Pierce, scoredOverPoints, 26000]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: scoredOverPoints Context triple: [Paul Pierce, scoredOverPoints, 26000]
-
A.
scoredOverPointsCareer
chosen
Indicates that an entity (typically an athlete) accumulated more than a specified number of points over the course of their entire career.
-
B.
hasScoredFor
Indicates that one entity has scored points, goals, or similar achievements on behalf of another entity, such as a team, organization, or side.
-
C.
isScoreFor
Indicates that one value represents the score or result associated with a particular entity, event, or performance.
-
D.
totalPointsScored
Indicates the total number of points accumulated or scored by an entity over a defined period, event, or context.
-
E.
winnerPoints
Indicates the number of points earned by the winning participant or entity in a competition or event.
- 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_69a498f912008190a376a98b207b2071 |
completed | March 1, 2026, 7:52 p.m. |
| NER | Named-entity recognition | batch_69a4c2d1d15481909d58b6fd8aa2e585 |
completed | March 1, 2026, 10:50 p.m. |
| PD | Predicate disambiguation | batch_69a4bef945c08190a027472fdd695ea5 |
completed | March 1, 2026, 10:34 p.m. |
Created at: March 1, 2026, 7:57 p.m.