Triple

T8835618
Position Surface form Disambiguated ID Type / Status
Subject ABA All-Time Team E210259 entity
Predicate player P30628 FINISHED
Object Roger Brown E122792 NE 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: Roger Brown | Statement: [ABA All-Time Team, player, Roger Brown]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Roger Brown
Context triple: [ABA All-Time Team, player, Roger Brown]
  • A. Roger Brown chosen
    Roger Brown was a professional basketball player best known for his scoring and rebounding in the American Basketball Association during the 1970s.
  • B. Roger Brown
    Roger Brown was an influential American social psychologist and linguist known for his pioneering research on language acquisition and the social psychology of language.
  • C. Arthur Johnson
    Arthur Johnson is a collegiate sports administrator who serves as the athletic director overseeing Temple University's athletics program, including the men's basketball team.
  • D. Roscoe Lee Browne
    Roscoe Lee Browne was an American actor and director known for his rich, distinctive voice and acclaimed performances in film, television, and theater.
  • E. Clarence Gilyard Jr.
    Clarence Gilyard Jr. was an American actor and academic best known for his roles in popular television series and action films such as "Matlock," "Walker, Texas Ranger," "Die Hard," and "Top Gun."
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

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_69ca8388549c819095fd94eadefbb007 completed March 30, 2026, 2:07 p.m.
NER Named-entity recognition batch_69cc6069ad7881909e31010e73e26f91 completed April 1, 2026, 12:01 a.m.
NED1 Entity disambiguation (via context triple) batch_69cf898022c88190b7274350ce065f00 completed April 3, 2026, 9:33 a.m.
Created at: March 30, 2026, 6:47 p.m.