Triple

T22745868
Position Surface form Disambiguated ID Type / Status
Subject Calbert Cheaney E562551 entity
Predicate pointsScoredInCollegeCareer P149587 FINISHED
Object 2650+ 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: 2650+ | Statement: [Calbert Cheaney, pointsScoredInCollegeCareer, 2650+]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: pointsScoredInCollegeCareer
Context triple: [Calbert Cheaney, pointsScoredInCollegeCareer, 2650+]
  • A. scoredPointsPerGameInCollege
    Indicates the average number of points an entity (typically an athlete) scored per game during their college career.
  • B. positionPlayedInCollege
    Indicates the specific playing position an individual held on a sports team during their college career.
  • C. playedCollegeYears
    Indicates the span of years during which an entity participated in college-level play (e.g., as a student-athlete).
  • D. playedForCollegeTeamUntil
    Indicates that an individual was a member of and played for a specific college team up to (and including) a particular end date or season.
  • E. scoredOverPointsCareer
    Indicates that an entity (typically an athlete) accumulated more than a specified number of points over the course of their entire career.
  • F. None of above. chosen

Provenance (4 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_69e245513a5c81908d5cb471b4fc429d completed April 17, 2026, 2:36 p.m.
NER Named-entity recognition batch_69f179b563e481908804d07fca1777b9 completed April 29, 2026, 3:23 a.m.
PD Predicate disambiguation batch_69eed2b88d88819096015deb6a648801 completed April 27, 2026, 3:06 a.m.
PDg Predicate description generation batch_69eeeb5681f88190821129ced752f190 completed April 27, 2026, 4:51 a.m.
Created at: April 17, 2026, 3:23 p.m.