Triple

T2877554
Position Surface form Disambiguated ID Type / Status
Subject Bonnie Bernstein E56913 entity
Predicate name P16 FINISHED
Object Bonnie Bernstein E56913 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: Bonnie Bernstein | Statement: [Bonnie Bernstein, name, Bonnie Bernstein]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Bonnie Bernstein
Context triple: [Bonnie Bernstein, name, Bonnie Bernstein]
  • A. Bonnie Bernstein chosen
    Bonnie Bernstein is an American sports journalist and television personality known for her sideline reporting and coverage of major events across networks like ESPN and CBS.
  • B. Bonnie Perlman
    Bonnie Perlman is an actress known for appearing in the television series "Obsessed."
  • C. Bonnie Sherr Klein
    Bonnie Sherr Klein is a Canadian filmmaker, writer, and disability rights activist known for her influential documentaries and advocacy work.
  • D. Barbara Bosson
    Barbara Bosson was an American actress best known for her Emmy-nominated role as Fay Furillo on the groundbreaking police drama "Hill Street Blues."
  • E. Gail Berman
    Gail Berman is an American television and film producer and media executive known for her influential roles at major studios and for producing high-profile projects across network TV and Hollywood.
  • 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_69ab4a4ced288190ab6d3e062d10f7f6 completed March 6, 2026, 9:42 p.m.
NER Named-entity recognition batch_69abe007329c8190b0bc1851c7307124 completed March 7, 2026, 8:21 a.m.
NED1 Entity disambiguation (via context triple) batch_69b5a81796fc8190b96e1feff3a73cba completed March 14, 2026, 6:25 p.m.
Created at: March 6, 2026, 10:03 p.m.