Triple

T8766664
Position Surface form Disambiguated ID Type / Status
Subject Disturbing Behavior E208354 entity
Predicate editor P1954 FINISHED
Object Marshall Harvey E404669 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: Marshall Harvey | Statement: [Disturbing Behavior, editor, Marshall Harvey]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Marshall Harvey
Context triple: [Disturbing Behavior, editor, Marshall Harvey]
  • A. Marshall Harvey chosen
    Marshall Harvey is a film editor best known for his work on movies such as the dark comedy "The 'Burbs."
  • B. Marshall Pease
    Marshall Pease is a computer scientist best known for co-authoring the seminal paper that introduced the Byzantine Generals Problem in distributed computing and fault tolerance.
  • C. Marshall Thompson
    Marshall Thompson was an American film and television actor best known for his roles in mid-20th-century Hollywood productions, including war dramas and science fiction films.
  • D. Marshall Bell
    Marshall Bell is an American character actor known for his memorable supporting roles in films such as Total Recall, Stand by Me, and A Nightmare on Elm Street 2.
  • E. Harvey Shephard
    Harvey Shephard is a television producer best known for his executive production work on the prime-time soap opera "Falcon Crest."
  • 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_69ca835df7e08190ac875664cca8f9ca completed March 30, 2026, 2:06 p.m.
NER Named-entity recognition batch_69cc5ee97fd0819087ef8fe14b37ae43 completed March 31, 2026, 11:55 p.m.
NED1 Entity disambiguation (via context triple) batch_69cfa033e1b4819083521484f46078a1 completed April 3, 2026, 11:10 a.m.
Created at: March 30, 2026, 6:41 p.m.