Triple

T5043471
Position Surface form Disambiguated ID Type / Status
Subject Gun Battle at Monterey E113601 entity
Predicate hasCastMember P2308 FINISHED
Object Pamela Duncan E689976 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: Pamela Duncan | Statement: [Gun Battle at Monterey, hasCastMember, Pamela Duncan]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Pamela Duncan
Context triple: [Gun Battle at Monterey, hasCastMember, Pamela Duncan]
  • A. Pamela Duncan chosen
    Pamela Duncan was an American film and television actress active in the 1950s and 1960s, known for her roles in low-budget Westerns and genre pictures.
  • B. Pamela Martin
    Pamela Martin is an American film editor known for her work on acclaimed movies such as "The Fighter" and "Little Miss Sunshine."
  • C. Pamela Tiffin
    Pamela Tiffin was an American film and television actress best known for her work in 1960s Hollywood comedies and dramas, as well as later Italian cinema.
  • D. Pamela Brown
    Pamela Brown was a British stage and film actress known for her intense character roles in mid-20th-century cinema and theatre.
  • E. Pamela Price
    Pamela Price is a civil rights attorney and progressive politician who serves as the elected District Attorney of Alameda County, California.
  • 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_69bd44391fc48190a311ce9c826c209b completed March 20, 2026, 12:57 p.m.
NER Named-entity recognition batch_69bd73fc04f08190aba851fa0192d0fb completed March 20, 2026, 4:21 p.m.
NED1 Entity disambiguation (via context triple) batch_69c91b0ad9188190ad74c33802f50783 completed March 29, 2026, 12:28 p.m.
Created at: March 20, 2026, 1:37 p.m.