Triple

T5269544
Position Surface form Disambiguated ID Type / Status
Subject Micka E119222 entity
Predicate hasSpellingVariant P457 FINISHED
Object Mickaʹ E119222 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: Mickaʹ | Statement: [Micka, hasSpellingVariant, Mickaʹ]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Mickaʹ
Context triple: [Micka, hasSpellingVariant, Mickaʹ]
  • A. Micka chosen
    Micka is a diminutive or affectionate nickname commonly used for the given name Michael.
  • B. Michal
    Michal is a biblical figure, a daughter of King Saul who became the first wife of King David in the Hebrew Bible.
  • C. Michal
    Michal is a mentally impaired and childlike character in Martin McDonagh’s dark play "The Pillowman," whose actions and relationship with his brother Katurian are central to the story’s moral and emotional conflict.
  • D. Miková
    Miková is a small village in northeastern Slovakia, notable as the birthplace of Julia Warhola, mother of artist Andy Warhol.
  • E. Mila
    Mila is a leading artificial intelligence research institute based in Quebec, renowned for its work in deep learning and machine learning.
  • 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_69bd446c38e081908cdaf113bdf86790 completed March 20, 2026, 12:58 p.m.
NER Named-entity recognition batch_69bd7bfdc9bc81908307f44f32fe9338 completed March 20, 2026, 4:55 p.m.
NED1 Entity disambiguation (via context triple) batch_69befe9542488190b715bc4bd800cb02 completed March 21, 2026, 8:24 p.m.
Created at: March 20, 2026, 1:51 p.m.