Triple

T11082439
Position Surface form Disambiguated ID Type / Status
Subject Ava Morse E262034 entity
Predicate voiceRole P12691 FINISHED
Object Miriam Mendelsohn E316906 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: Miriam Mendelsohn | Statement: [Ava Morse, voiceRole, Miriam Mendelsohn]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Miriam Mendelsohn
Context triple: [Ava Morse, voiceRole, Miriam Mendelsohn]
  • A. Miriam Mendelsohn chosen
    Miriam Mendelsohn is a loyal, upbeat, and supportive best friend of Mei Lee in Pixar's animated film "Turning Red."
  • B. Miriam Fried
    Miriam Fried is an acclaimed Israeli-American violinist renowned for her solo performances, chamber music collaborations, and influential teaching career.
  • C. Miriam Bienstock
    Miriam Bienstock was an American music industry executive and co-founder of Atlantic Records who played a key role in shaping the label’s early business operations and success.
  • D. Miriam Weinstein
    Miriam Weinstein is the mother of film producer Harvey Weinstein, whose first name inspired the name of the film company Miramax.
  • E. Helene Shapiro
    Helene Shapiro is an American mathematician known for her work in linear algebra and matrix theory, and as a student of Olga Taussky-Todd.
  • 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_69d6aa9983c08190b0ef61603b69feac completed April 8, 2026, 7:20 p.m.
NER Named-entity recognition batch_69d799985650819089b2c0f35a212414 completed April 9, 2026, 12:20 p.m.
NED1 Entity disambiguation (via context triple) batch_69e5b76fa8348190bb42f1c71eb0e545 completed April 20, 2026, 5:19 a.m.
Created at: April 8, 2026, 9:27 p.m.