Triple

T16190950
Position Surface form Disambiguated ID Type / Status
Subject Emmanuelle Chriqui E392936 entity
Predicate notableWork P4 FINISHED
Object Cleaners E1006438 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: Cleaners | Statement: [Emmanuelle Chriqui, notableWork, Cleaners]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Cleaners
Context triple: [Emmanuelle Chriqui, notableWork, Cleaners]
  • A. Cleaners chosen
    Cleaners is a crime thriller web series featuring Gina Gershon in a lead role as a professional assassin.
  • B. The Cleaner
    The Cleaner is a crime drama television series centered on a recovering addict who leads an unconventional team that helps people overcome their addictions through often morally ambiguous interventions.
  • C. Take ‘Em to the Cleaners
    Take ‘Em to the Cleaners is a release by the hip hop group Consequence, showcasing his lyrical style and contributions to the genre.
  • D. Schoonmaker
    Schoonmaker is a Dutch-origin surname most notably borne by acclaimed film editor Thelma Schoonmaker.
  • E. The Removers
    The Removers is a 1961 spy novel by Donald Hamilton, part of his long-running Matt Helm series featuring a hard-edged American government assassin.
  • 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_69d87f1e49ac8190a311b54d32990576 completed April 10, 2026, 4:39 a.m.
NER Named-entity recognition batch_69e222d5769c8190bbb604bfa095a1a5 completed April 17, 2026, 12:08 p.m.
NED1 Entity disambiguation (via context triple) batch_69ffff095504819096c36d6c5d131207 completed May 10, 2026, 3:44 a.m.
Created at: April 10, 2026, 5:02 a.m.