Triple

T19687238
Position Surface form Disambiguated ID Type / Status
Subject Barney Green E472742 entity
Predicate name P16 FINISHED
Object Barney Green 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: Barney Green | Statement: [Barney Green, name, Barney Green]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Barney Green
Context triple: [Barney Green, name, Barney Green]
  • A. Barney Green chosen
    Barney Green was an elderly Irish civilian who became widely known as one of the victims killed in the 1994 Loughinisland massacre in County Down, Northern Ireland.
  • B. Barney McGill
    Barney McGill was an American cinematographer known for his influential work in early Hollywood and for helping to establish the American Society of Cinematographers.
  • C. Barney Wile
    Barney Wile is a fictional character appearing in the classic 1949 baseball drama film "The Stratton Story."
  • D. Barney Felix
    Barney Felix was an American boxing referee best known for officiating high-profile bouts during the mid-20th century, including championship fights featuring Muhammad Ali.
  • E. Barney Phillips
    Barney Phillips was an American character actor known for his numerous television roles from the 1950s through the 1970s, including memorable appearances on series like "The Twilight Zone."
  • 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_69d8e515bef88190bc30781aea50537a completed April 10, 2026, 11:55 a.m.
NER Named-entity recognition batch_69e6420d39688190ad3a84dbffce4ffe completed April 20, 2026, 3:11 p.m.
Created at: April 10, 2026, 1:45 p.m.