Triple

T7590779
Position Surface form Disambiguated ID Type / Status
Subject Nora Stanton Blatch E179729 entity
Predicate familyName P18 FINISHED
Object Blatch E35442 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: Blatch | Statement: [Nora Stanton Blatch, familyName, Blatch]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Blatch
Context triple: [Nora Stanton Blatch, familyName, Blatch]
  • A. Blatch chosen
    Blatch is the surname of Nora Stanton Blatch, an early 20th-century American civil engineer, suffragist, and women's rights activist.
  • B. Blagg
    Blagg is a variant form of the surname "Black," typically arising as an alternative spelling in English-speaking regions.
  • C. Blix
    Blix is a 19th-century novel by American naturalist writer Frank Norris that follows a young woman’s coming-of-age and romantic experiences in San Francisco.
  • D. Blix
    Blix is a Swedish surname most notably associated with Hans Blix, the former head of the International Atomic Energy Agency and UN weapons inspector.
  • E. Beyton
    Beyton is a small rural village and civil parish in the English county of Suffolk, known for its traditional village green and historic buildings.
  • 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_69c69f335248819093c1006f30513708 completed March 27, 2026, 3:16 p.m.
NER Named-entity recognition batch_69c6f9b615f481908b2fe7e8aaed81bc completed March 27, 2026, 9:42 p.m.
NED1 Entity disambiguation (via context triple) batch_69c86192b5d88190b0a02cf303462bfb completed March 28, 2026, 11:17 p.m.
Created at: March 27, 2026, 3:53 p.m.