Triple

T18226399
Position Surface form Disambiguated ID Type / Status
Subject NFL Game of the Week E436432 entity
Predicate narrationBy P2181 FINISHED
Object Jim Lampley NE NERFINISHED

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: Jim Lampley | Statement: [NFL Game of the Week, narrationBy, Jim Lampley]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Jim Lampley
Context triple: [NFL Game of the Week, narrationBy, Jim Lampley]
  • A. Jim Lampley chosen
    Jim Lampley is an American sportscaster and television personality best known for his long tenure as a boxing commentator on HBO.
  • B. Kenny Albert
    Kenny Albert is an American sportscaster known for his play-by-play work across major sports leagues, including the NFL, NHL, MLB, and NBA.
  • C. Marv Albert
    Marv Albert is a renowned American sportscaster best known as the longtime voice of NBA basketball and a prominent play-by-play announcer across multiple major sports.
  • D. Chris Berman
    Chris Berman is a longtime ESPN sportscaster best known for his energetic NFL coverage and signature catchphrases.
  • E. Kevin Burns
    Kevin Burns was an American television producer and documentarian best known for creating and producing numerous history- and science-themed series, including "Ancient Aliens" and various programs for the History Channel.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69d8b9103a8081908bbb0836fef10efd completed April 10, 2026, 8:47 a.m.
NER Named-entity recognition batch_69e4f4aff8748190be5e732f9dbc8dff completed April 19, 2026, 3:28 p.m.
Created at: April 10, 2026, 10:32 a.m.