Triple

T21961579
Position Surface form Disambiguated ID Type / Status
Subject María E542342 entity
Predicate hasVariant 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: [María, hasVariant, Miriam]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Miriam
Context triple: [María, hasVariant, 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 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.
  • C. Miriam
    Miriam is a fictional character from the British dark comedy television series "The Life and Times of Vivienne Vyle."
  • D. Miriam chosen
    Miriam is the birth name of American country music singer and songwriter Jessi Colter.
  • E. Miriam
    Miriam is a key supporting character in Lew Wallace's novel "Ben-Hur: A Tale of the Christ," serving as Judah Ben-Hur's mother and a central figure in his personal trials and motivations.
  • 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_69e0c47fab1081908dc74a6545dbb051 completed April 16, 2026, 11:14 a.m.
NER Named-entity recognition batch_69f124572738819098cc669aafa53cc6 completed April 28, 2026, 9:19 p.m.
Created at: April 16, 2026, 8 p.m.