Triple

T20331181
Position Surface form Disambiguated ID Type / Status
Subject Trudy Campbell E492484 entity
Predicate creator P184 FINISHED
Object Matthew Weiner NE NERFINISHED

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: [Trudy Campbell, creator, Matthew Weiner]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Matthew Weiner
Context triple: [Trudy Campbell, 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. Matthew Wiener
    Matthew Wiener is a statistician and software developer known for his contributions to the R community, including work on the randomForest package for machine learning.
  • C. Sam Levinson
    Sam Levinson is an American filmmaker, screenwriter, and director best known for creating the HBO teen drama series "Euphoria."
  • D. Jake Weiner
    Jake Weiner is a film producer known for his work on major studio projects, including Disney’s live-action adaptation of Mulan (2020).
  • E. John Slattery
    John Slattery is an American actor and director best known for his role as Roger Sterling on the television series "Mad Men."
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69e0b4a1a09881908d97270d6971a25a completed April 16, 2026, 10:06 a.m.
NER Named-entity recognition batch_69e677e7baf481909282293d78597634 completed April 20, 2026, 7 p.m.
Created at: April 16, 2026, 11:22 a.m.