Triple
T10239367
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jimmer Fredette |
E243546
|
entity |
| Predicate | collegeTeamSeasonPointsPerGame |
P38590
|
FINISHED |
| Object | 28.9 (2010–11 season) |
—
|
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: 28.9 (2010–11 season) | Statement: [Jimmer Fredette, collegeTeamSeasonPointsPerGame, 28.9 (2010–11 season)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: collegeTeamSeasonPointsPerGame Context triple: [Jimmer Fredette, collegeTeamSeasonPointsPerGame, 28.9 (2010–11 season)]
-
A.
collegeTeamPointsPerGameLeader
Indicates the player who leads a college team in average points scored per game.
-
B.
collegeTeamPoints
Indicates the number of points scored or accumulated by a college sports team in a particular game, season, or competition.
-
C.
collegeTeamPointsRecordHolder
Indicates that the subject is the record-holding individual or team for the highest number of points scored for a particular college team.
-
D.
collegeTeamAssists
Indicates that one college sports team provides assistance or support to another team.
-
E.
scoredPointsPerGameInCollege
chosen
Indicates the average number of points an entity (typically an athlete) scored per game during their college career.
- 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_69d381b0f97c819085c9b45799a5fb7c |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d4d328272c8190a3548d7f7f38cfc4 |
completed | April 7, 2026, 9:49 a.m. |
| PD | Predicate disambiguation | batch_69d4d1ebd6c88190a1f3f4a72a99d6fe |
completed | April 7, 2026, 9:44 a.m. |
Created at: April 6, 2026, 11:23 a.m.