Triple

T15709950
Position Surface form Disambiguated ID Type / Status
Subject Gale Weathers E380811 entity
Predicate setting P1957 FINISHED
Object Woodsboro E380814 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: Woodsboro | Statement: [Gale Weathers, setting, Woodsboro]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Woodsboro
Context triple: [Gale Weathers, setting, Woodsboro]
  • A. Woodsboro chosen
    Woodsboro is the fictional small town that serves as the primary setting for much of the Scream horror film franchise.
  • B. Haddonfield
    Haddonfield is a historic suburban borough in Camden County, New Jersey, known for its charming downtown, colonial-era architecture, and strong community character.
  • C. Plainville
    Plainville is a small suburban town in central Connecticut, known for its residential character and proximity to the city of Hartford.
  • D. Clayburgh
    Clayburgh is a surname most notably associated with American actress Jill Clayburgh, known for her acclaimed film and stage performances in the 1970s and 1980s.
  • E. Murphyville
    Murphyville was the original name of Alpine, a small city in West Texas known as a gateway to the Big Bend region.
  • 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_69d86d9bf930819082b30cf6d169297c completed April 10, 2026, 3:25 a.m.
NER Named-entity recognition batch_69e04f8d8b648190842c635f2ae7bfa4 completed April 16, 2026, 2:55 a.m.
NED1 Entity disambiguation (via context triple) batch_69ff82f22fc88190820ecb171041136d completed May 9, 2026, 6:54 p.m.
Created at: April 10, 2026, 4:45 a.m.