Triple

T10973562
Position Surface form Disambiguated ID Type / Status
Subject Michael Myers E259308 entity
Predicate createdBy P806 FINISHED
Object Debra Hill E285696 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: Debra Hill | Statement: [Michael Myers, createdBy, Debra Hill]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Debra Hill
Context triple: [Michael Myers, createdBy, Debra Hill]
  • A. Debra Hill chosen
    Debra Hill was an American film producer and screenwriter best known for co-writing and producing influential horror films such as "Halloween" alongside John Carpenter.
  • B. Diane Chambers
    Diane Chambers is an intelligent, sophisticated, and often pretentious waitress and love interest of Sam Malone on the classic American sitcom "Cheers."
  • C. Debbie Aldridge
    Debbie Aldridge is a fictional character from the long-running BBC Radio 4 soap opera "The Archers."
  • D. Debbie Edwards
    Debbie Edwards is the kidnapped niece whose years-long search drives the emotional core of John Ford’s classic Western film "The Searchers."
  • E. Debralee Scott
    Debralee Scott was an American actress best known for her comedic roles on 1970s and 1980s television sitcoms and films.
  • 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_69d6aa895f4c8190887a15460ef622f4 completed April 8, 2026, 7:20 p.m.
NER Named-entity recognition batch_69d7719c16648190ab5a87abb1c61990 completed April 9, 2026, 9:30 a.m.
NED1 Entity disambiguation (via context triple) batch_69e2d7a0b3dc819084fbda3227caf5b5 completed April 18, 2026, 1 a.m.
Created at: April 8, 2026, 9:24 p.m.