Triple
T20075201
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Joe Fulks |
E499843
|
entity |
| Predicate | totalPointsCareer |
P27224
|
FINISHED |
| Object | 8076 |
—
|
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: 8076 | Statement: [Joe Fulks, totalPointsCareer, 8076]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: totalPointsCareer Context triple: [Joe Fulks, totalPointsCareer, 8076]
-
A.
totalCareerPointsNBA
Indicates the total number of points a player has scored over their entire NBA career.
-
B.
NBA_careerPoints
chosen
Indicates the total number of points a player has scored over the course of their NBA career.
-
C.
scoredOverPointsCareer
Indicates that an entity (typically an athlete) accumulated more than a specified number of points over the course of their entire career.
-
D.
careerPoints
Indicates the total number of points an individual has accumulated over the course of their entire career in a given activity or domain.
-
E.
totalPointsScored
Indicates the total number of points accumulated or scored by an entity over a defined period, event, or context.
- 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_69da627770948190997f486f9a2e370f |
completed | April 11, 2026, 3:02 p.m. |
| NER | Named-entity recognition | batch_69e6643ab0448190ab18d013b72aaf32 |
completed | April 20, 2026, 5:36 p.m. |
| PD | Predicate disambiguation | batch_69e54cf369b88190931532420517dac7 |
completed | April 19, 2026, 9:45 p.m. |
Created at: April 11, 2026, 3:40 p.m.