Triple

T15099279
Position Surface form Disambiguated ID Type / Status
Subject New Girl in Town E360618 entity
Predicate hasCharacterFromSource P72229 FINISHED
Object Mat Burke E934470 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: Mat Burke | Statement: [New Girl in Town, hasCharacterFromSource, Mat Burke]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Mat Burke
Context triple: [New Girl in Town, hasCharacterFromSource, Mat Burke]
  • A. Mat Burke chosen
    Mat Burke is a central character in Eugene O’Neill’s play "Anna Christie," portrayed as a rugged Irish stoker whose passionate relationship with Anna drives much of the drama’s emotional conflict.
  • B. Dave Burke
    Dave Burke is a central character in the 1959 film noir "Odds Against Tomorrow," depicted as a former police officer who masterminds a high-stakes bank heist.
  • C. Warren Burke
    Warren Burke is an actor known for his role in the Western film "Dead for a Dollar."
  • D. Sam Daly
    Sam Daly is an American actor known for roles in film and television and as the son of actor Tim Daly.
  • E. Phil Burke
    Phil Burke is a Canadian actor best known for his role as Mickey McGinnes on the television drama series "Hell on Wheels."
  • 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_69d85a035aa88190b52a139d3a1b7b6d completed April 10, 2026, 2:01 a.m.
NER Named-entity recognition batch_69e0054f00388190a5123d9f4a869b96 completed April 15, 2026, 9:38 p.m.
NED1 Entity disambiguation (via context triple) batch_69ff6ec2f35c8190a96af080cd7b6d0e completed May 9, 2026, 5:28 p.m.
Created at: April 10, 2026, 3:04 a.m.