Triple

T19828979
Position Surface form Disambiguated ID Type / Status
Subject Sarah Parish E476404 entity
Predicate notableWork P4 FINISHED
Object Cutting It 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: Cutting It | Statement: [Sarah Parish, notableWork, Cutting It]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Cutting It
Context triple: [Sarah Parish, notableWork, Cutting It]
  • A. Cutting It chosen
    Cutting It is a British television drama series centered on the personal and professional lives of rival hairdressing salon owners in Manchester.
  • B. Cuttin Up
    Cuttin Up is a breakout drill track by Chicago rapper Lud Foe that helped establish his aggressive, street-oriented style and grow his underground following.
  • C. The Cut
    The Cut is a street in the Waterloo area of London known for its theatres, restaurants, and proximity to major transport links.
  • D. The Cut
    The Cut is a 2014 historical drama film directed by Fatih Akin that follows an Armenian man's search for his daughters in the aftermath of the Armenian genocide.
  • E. The Cut
    The Cut is a digital publication and vertical of New York Magazine that focuses on fashion, culture, politics, and women’s issues.
  • 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_69d8e51c7c188190b926f3a2a7b5f881 completed April 10, 2026, 11:55 a.m.
NER Named-entity recognition batch_69e656ccd3748190adeaed9a431f8979 completed April 20, 2026, 4:39 p.m.
Created at: April 10, 2026, 1:50 p.m.