Triple

T4441134
Position Surface form Disambiguated ID Type / Status
Subject Junior E95772 entity
Predicate editedBy P1954 FINISHED
Object Wendy Greene Bricmont E252830 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: Wendy Greene Bricmont | Statement: [Junior, editedBy, Wendy Greene Bricmont]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Wendy Greene Bricmont
Context triple: [Junior, editedBy, Wendy Greene Bricmont]
  • A. Wendy Greene Bricmont chosen
    Wendy Greene Bricmont is an American film editor best known for her work on influential films such as Woody Allen’s "Annie Hall."
  • B. Wendy Hall
    Wendy Hall is a pioneering British computer scientist and professor known for her influential work in hypermedia, the World Wide Web, and web science.
  • C. Sonia H. Greene
    Sonia H. Greene was a Ukrainian-born American writer, amateur publisher, and businesswoman best known for her association and brief marriage to horror author H. P. Lovecraft.
  • D. Wendy Steiner
    Wendy Steiner is an American literary critic and scholar known for her influential work on aesthetics, modernism, and the relationship between visual art and literature.
  • E. Lynne Overman
    Lynne Overman was an American character actor of the 1930s and 1940s, known for his supporting roles in Hollywood films and his distinctive, wisecracking screen persona.
  • 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_69b3453ea2b48190a26f154b3b8fece5 completed March 12, 2026, 10:59 p.m.
NER Named-entity recognition batch_69b355ad71588190b1dcad4250472c29 completed March 13, 2026, 12:09 a.m.
NED1 Entity disambiguation (via context triple) batch_69b6281264f08190942d2043495c89d5 completed March 15, 2026, 3:31 a.m.
Created at: March 12, 2026, 11:32 p.m.