Triple

T11344217
Position Surface form Disambiguated ID Type / Status
Subject Sally Draper E268676 entity
Predicate creator P184 FINISHED
Object Matthew Weiner E268664 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: Matthew Weiner | Statement: [Sally Draper, creator, Matthew Weiner]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Matthew Weiner
Context triple: [Sally Draper, creator, Matthew Weiner]
  • A. Matthew Weiner chosen
    Matthew Weiner is an American television writer, director, and producer best known for creating the critically acclaimed series "Mad Men."
  • B. Sam Levinson
    Sam Levinson is an American filmmaker, screenwriter, and director best known for creating the HBO teen drama series "Euphoria."
  • C. John Slattery
    John Slattery is an American actor and director best known for his role as Roger Sterling on the television series "Mad Men."
  • D. Donald Faison
    Donald Faison is an American actor and comedian best known for his role as Dr. Christopher Turk on the television series "Scrubs."
  • E. David Margulies
    David Margulies was an American character actor known for his roles in films such as Ghostbusters and numerous appearances on stage and television.
  • 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_69d6aacbe18081909e5fadb50082dd96 completed April 8, 2026, 7:21 p.m.
NER Named-entity recognition batch_69d7ea1f9574819089760c5b5908f09e completed April 9, 2026, 6:04 p.m.
NED1 Entity disambiguation (via context triple) batch_69e6e72931208190b91ef4be770c00d4 completed April 21, 2026, 2:55 a.m.
Created at: April 8, 2026, 9:33 p.m.