Triple

T22637913
Position Surface form Disambiguated ID Type / Status
Subject Kyra D. Morris E558731 entity
Predicate workedOn P3 FINISHED
Object Cuts 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: Cuts | Statement: [Kyra D. Morris, workedOn, Cuts]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Cuts
Context triple: [Kyra D. Morris, workedOn, Cuts]
  • A. Cuts chosen
    Cuts is an American television sitcom that aired on UPN, featuring Shannon Elizabeth in a comedic role set around a family-owned barbershop.
  • B. CUT
    CUT is the National Rail station code assigned to Cutty Sark DLR station in London.
  • C. CUT
    CUT is the IATA airport code for Cutral Có Airport, which serves the city of Cutral Có in Neuquén Province, Argentina.
  • D. CUT
    CUT is the commonly used acronym for the Central Unitaria de Trabajadores, a major national trade union federation.
  • E. CUT
    CUT is the commonly used acronym for the Central University of Technology, a higher education institution in South Africa.
  • 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_69e24547f7fc819086e2c4ba3b979657 completed April 17, 2026, 2:35 p.m.
NER Named-entity recognition batch_69f1700edb608190ad786ff7fafea0da completed April 29, 2026, 2:42 a.m.
Created at: April 17, 2026, 3:04 p.m.