Triple
T8089990
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lionel Simmons |
E188831
|
entity |
| Predicate | scoringMilestone |
P52327
|
FINISHED |
| Object | one of NCAA Division I all-time leading scorers |
—
|
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: one of NCAA Division I all-time leading scorers | Statement: [Lionel Simmons, scoringMilestone, one of NCAA Division I all-time leading scorers]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: scoringMilestone Context triple: [Lionel Simmons, scoringMilestone, one of NCAA Division I all-time leading scorers]
-
A.
hitsMilestone
chosen
Indicates that an entity reaches or achieves a predefined milestone or target in a process, project, or progression.
-
B.
scoringRecord
Indicates that there exists a record documenting a scoring event or outcome associated with the given entities.
-
C.
scoringLeaderPoints
Indicates the number of points scored by the leading scorer in a game, season, or competition.
-
D.
scoring
Indicates the act of achieving points or a measurable result, typically by successfully completing an action that contributes to a score or outcome.
-
E.
scoringUnit
Indicates that one entity functions as a unit or component responsible for scoring or assigning scores to another entity.
- 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.