Triple
T8089982
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lionel Simmons |
E188831
|
entity |
| Predicate | collegePointsScored |
P17024
|
FINISHED |
| Object | over 3000 |
—
|
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: over 3000 | Statement: [Lionel Simmons, collegePointsScored, over 3000]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: collegePointsScored Context triple: [Lionel Simmons, collegePointsScored, over 3000]
-
A.
pointsScored
Indicates the number of points an entity has earned or achieved in a particular event, game, or context.
-
B.
totalPointsScored
chosen
Indicates the total number of points accumulated or scored by an entity over a defined period, event, or context.
-
C.
scoredPointsPerGameInCollege
Indicates the average number of points an entity (typically an athlete) scored per game during their college career.
-
D.
JetsScore
Indicates that the team named Jets scores a certain number of points in a game or event.
-
E.
teamScoring
Indicates that a team achieves a score or points in a game, match, or competitive 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_69ca82b7b3e88190b9041ab0ef28b3cb |
completed | March 30, 2026, 2:03 p.m. |
| NER | Named-entity recognition | batch_69cb421e30e88190b9699b338b69b81c |
completed | March 31, 2026, 3:40 a.m. |
| PD | Predicate disambiguation | batch_69cb04a14cd88190a79ed26cbeec1c33 |
completed | March 30, 2026, 11:17 p.m. |
Created at: March 30, 2026, 5:29 p.m.