Triple

T9238019
Position Surface form Disambiguated ID Type / Status
Subject Office Christmas Party E221984 entity
Predicate cinematographyBy P1953 FINISHED
Object Jeff Cutter E418033 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: Jeff Cutter | Statement: [Office Christmas Party, cinematographyBy, Jeff Cutter]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Jeff Cutter
Context triple: [Office Christmas Party, cinematographyBy, Jeff Cutter]
  • A. Jeff Cutter chosen
    Jeff Cutter is an American cinematographer known for his work on genre films such as the thriller "10 Cloverfield Lane."
  • B. Michael Cutter
    Michael Cutter is a fictional executive assistant district attorney known for his aggressive, hard-driving prosecution style on the television series "Law & Order."
  • C. Grant Cutler
    Grant Cutler is a musician best known as a member of the indie supergroup Gayngs, contributing to its atmospheric, genre-blending sound.
  • D. John Ketcham
    John Ketcham is a film producer best known for his work on the biographical sports drama "The Hurricane."
  • E. James Cutler
    James Cutler is an architect best known for designing the Salem Witch Trials Memorial in Salem, Massachusetts.
  • 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_69ca83ee26cc81909ac624e190597d6d completed March 30, 2026, 2:08 p.m.
NER Named-entity recognition batch_69ccf09f9e908190801fe114c5e63984 completed April 1, 2026, 10:17 a.m.
NED1 Entity disambiguation (via context triple) batch_69d077d4c4a881909c80176ddf5101a4 completed April 4, 2026, 2:30 a.m.
Created at: March 30, 2026, 7:30 p.m.