Triple

T14597938
Position Surface form Disambiguated ID Type / Status
Subject Maryanne E342621 entity
Predicate hasSpellingVariant P457 FINISHED
Object Maryann E342621 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: Maryann | Statement: [Maryanne, hasSpellingVariant, Maryann]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Maryann
Context triple: [Maryanne, hasSpellingVariant, Maryann]
  • A. Mariann
    Mariann is the given name of Mariann Edgar Budde, an American Episcopal bishop known for her leadership in the Episcopal Diocese of Washington.
  • B. Maryanne chosen
    Maryanne is a feminine given name, often used in English-speaking countries as a variant of Mary Ann or Marianne.
  • C. Marnie
    Marnie is a 1964 psychological thriller film directed by Alfred Hitchcock, starring Tippi Hedren and Sean Connery, about a troubled woman with a mysterious past and compulsive thieving.
  • D. Marnie
    Marnie is the given name of Darcey Bussell, the renowned British ballerina and former principal dancer of The Royal Ballet.
  • E. Marybeth
    Marybeth is a feminine given name, often considered a combination of Mary and Beth, used primarily in English-speaking countries.
  • 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_69d822ddc0f081909cd8163c7de298cd completed April 9, 2026, 10:06 p.m.
NER Named-entity recognition batch_69deb436d92881908fdf9267568feee2 completed April 14, 2026, 9:40 p.m.
NED1 Entity disambiguation (via context triple) batch_69fd94c81e608190848c290defcd84ac completed May 8, 2026, 7:46 a.m.
Created at: April 10, 2026, 1:25 a.m.