Triple

T9859611
Position Surface form Disambiguated ID Type / Status
Subject Myra, West Virginia E239675 entity
Predicate namedAfter P63 FINISHED
Object Myra (given name) E231447 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: Myra (given name) | Statement: [Myra, West Virginia, namedAfter, Myra (given name)]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Myra (given name)
Context triple: [Myra, West Virginia, namedAfter, Myra (given name)]
  • A. Myra (given name) chosen
    Myra is a feminine given name of English origin, often considered a poetic or invented name that gained popularity in the 17th century.
  • B. Myra Finn
    Myra Finn was the first wife of renowned American lyricist and musical theatre producer Oscar Hammerstein II.
  • C. Maryanne
    Maryanne is a feminine given name, often used in English-speaking countries as a variant of Mary Ann or Marianne.
  • D. Madelyn
    Madelyn is a feminine given name, often considered a modern variant of Madeline and commonly used in English-speaking countries.
  • E. Marilynne
    Marilynne is the given name of Marilynne Robinson, the acclaimed American novelist and essayist known for works such as "Housekeeping" and the "Gilead" series.
  • 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_69ca84e6493081909cf58c8d42ea856b completed March 30, 2026, 2:12 p.m.
NER Named-entity recognition batch_69cdb39b06b48190ab53ff00ff0513ca completed April 2, 2026, 12:08 a.m.
NED1 Entity disambiguation (via context triple) batch_69d1e4411a9481909657f522af7500ac completed April 5, 2026, 4:25 a.m.
Created at: March 30, 2026, 8:35 p.m.