Triple

T19846906
Position Surface form Disambiguated ID Type / Status
Subject Maria E476886 entity
Predicate isVariantOf P455 FINISHED
Object Miriam 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: Miriam | Statement: [Maria, isVariantOf, Miriam]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Miriam
Context triple: [Maria, isVariantOf, Miriam]
  • A. Miriam
    Miriam is a central fictional character in Nathaniel Hawthorne’s novel "The Marble Faun," portrayed as a mysterious and artistically gifted woman with a troubled past.
  • B. Miriam
    Miriam "Midge" Maisel is the quick-witted 1950s New York housewife-turned-stand-up-comedian who stars as the protagonist of the television series "The Marvelous Mrs. Maisel."
  • C. Miriam chosen
    Miriam is a prominent biblical figure known as the sister of Moses and Aaron and as a prophetess during the Exodus of the Israelites from Egypt.
  • D. Miriam
    Miriam is a fictional character from the British dark comedy television series "The Life and Times of Vivienne Vyle."
  • E. Miriam
    Miriam is the birth name of American country music singer and songwriter Jessi Colter.
  • 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_69d8e51d39d081909bcfafeaaf3d2fcc completed April 10, 2026, 11:55 a.m.
NER Named-entity recognition batch_69e65809da2c8190bb579ef42513b74d completed April 20, 2026, 4:44 p.m.
Created at: April 10, 2026, 1:51 p.m.