Triple

T9983745
Position Surface form Disambiguated ID Type / Status
Subject Streets of Fire E196514 entity
Predicate hasCastMember P2308 FINISHED
Object Amy Madigan E159006 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: Amy Madigan | Statement: [Streets of Fire, hasCastMember, Amy Madigan]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Amy Madigan
Context triple: [Streets of Fire, hasCastMember, Amy Madigan]
  • A. Amy Madigan chosen
    Amy Madigan is an American actress known for her Academy Award–nominated role in "Twice in a Lifetime" and performances in films such as "Field of Dreams" and "Uncle Buck."
  • B. Gail C. Murphy
    Gail C. Murphy is a prominent Canadian computer scientist known for her influential research in software engineering, particularly in improving developer productivity and software evolution.
  • C. Pat Murphy
    Pat Murphy is a name shared by several notable individuals, including an American science fiction and fantasy author and various sports figures.
  • D. Frances Rafferty
    Frances Rafferty was an American actress and dancer best known for her roles in 1940s MGM musicals and later in the television series "December Bride."
  • E. Maureen Beattie
    Maureen Beattie is a Scottish actress known for her extensive work in television, theatre, and film, including roles in British dramas and comedies.
  • 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_69ca82efbce081908179b4b9c65096eb completed March 30, 2026, 2:04 p.m.
NER Named-entity recognition batch_69cdb8bdc0388190bbbd4bdc5ac3adec completed April 2, 2026, 12:30 a.m.
NED1 Entity disambiguation (via context triple) batch_69d257f3c59481909b90896be0f3a870 completed April 5, 2026, 12:39 p.m.
Created at: March 30, 2026, 8:49 p.m.