Triple

T13753716
Position Surface form Disambiguated ID Type / Status
Subject Shirley Maisel E330419 entity
Predicate hasDaughterInLaw P31445 FINISHED
Object Miriam Maisel E1050599 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 Maisel | Statement: [Shirley Maisel, hasDaughterInLaw, Miriam Maisel]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Miriam Maisel
Context triple: [Shirley Maisel, hasDaughterInLaw, Miriam Maisel]
  • A. Miriam Maisel chosen
    Miriam Maisel is the quick-witted 1950s housewife-turned-stand-up comedian who serves as the protagonist of the television series "The Marvelous Mrs. Maisel."
  • B. Hilary Minc
    Hilary Minc was a prominent Polish communist politician and economist who played a leading role in shaping Poland’s post-World War II socialist economy.
  • C. Shirley Maisel
    Shirley Maisel is a comedic, overbearing, and traditional Jewish matriarch in the television series "The Marvelous Mrs. Maisel," known for her meddling nature and sharp-tongued humor.
  • D. Sarah Baldwin
    Sarah Baldwin is an actress known for appearing in the romantic comedy film "Something Borrowed."
  • E. Iliza Shlesinger
    Iliza Shlesinger is an American stand-up comedian, actress, and writer known for her sharp, high-energy comedy specials and roles in film 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_69d81c573f288190aa2403d484fa3d49 completed April 9, 2026, 9:38 p.m.
NER Named-entity recognition batch_69de0215cfa08190aaed8b089aff217b completed April 14, 2026, 9 a.m.
NED1 Entity disambiguation (via context triple) batch_69f7a85813e88190a63fecf8b0675df6 completed May 3, 2026, 7:56 p.m.
Created at: April 9, 2026, 10:09 p.m.