Triple

T14818018
Position Surface form Disambiguated ID Type / Status
Subject Rebecca Washington E348368 entity
Predicate hasColleague P398 FINISHED
Object Jimmy Berluti E336741 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: Jimmy Berluti | Statement: [Rebecca Washington, hasColleague, Jimmy Berluti]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Jimmy Berluti
Context triple: [Rebecca Washington, hasColleague, Jimmy Berluti]
  • A. Jimmy Berluti chosen
    Jimmy Berluti is a fictional attorney from the television legal drama "The Practice," known for his working-class background and moral struggles within the high-pressure world of criminal defense law.
  • B. Alessandro Berluti
    Alessandro Berluti was an Italian shoemaker and craftsman best known as the founder of the luxury footwear and leather goods brand Berluti.
  • C. George Furla
    George Furla is an American film producer known for financing and producing numerous independent and genre films through his company Emmett/Furla/Oasis Films.
  • D. Emanuel Ungaro
    Emanuel Ungaro was a renowned French fashion designer celebrated for his vibrant colors, bold prints, and sensuous, feminine silhouettes.
  • E. Leo Cattozzo
    Leo Cattozzo was an Italian film editor and inventor best known for creating the CIR-Cattozzo splicing machine, widely used in film editing.
  • 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_69d822eb8f588190bf53445e730a934f completed April 9, 2026, 10:06 p.m.
NER Named-entity recognition batch_69decfe2c1ec81908b3dff7a5d0e85d0 completed April 14, 2026, 11:38 p.m.
NED1 Entity disambiguation (via context triple) batch_69fe3897691c819085ef89480e730723 completed May 8, 2026, 7:25 p.m.
Created at: April 10, 2026, 1:50 a.m.