Triple

T22585011
Position Surface form Disambiguated ID Type / Status
Subject Unicode normalization E564765 entity
Predicate hasFullName P16 FINISHED
Object Normalization Form KC — NE NERFINISHED

How this triple was built (3 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: Normalization Form KC | Statement: [Unicode normalization, hasFullName, Normalization Form KC]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Normalization Form KC
Context triple: [Unicode normalization, hasFullName, Normalization Form KC]
  • A. Unicode normalization
    Unicode normalization is a set of standardized processes that convert equivalent Unicode text sequences into a consistent canonical form to ensure reliable comparison, searching, and processing of text across systems.
  • B. Alphabetic Presentation Forms
    Alphabetic Presentation Forms is a Unicode block that contains compatibility characters for various alphabetic scripts, primarily providing precomposed glyph variants used in legacy text encodings and typographic contexts.
  • C. CJK Unified Ideographs Extension A
    CJK Unified Ideographs Extension A is a Unicode block that adds additional rare and historic Chinese, Japanese, and Korean characters beyond those included in the main CJK Unified Ideographs block.
  • D. Unicode Standard Annex #38
    Unicode Standard Annex #38 is a technical report that defines the Unicode Han Database (Unihan), specifying data fields and properties for East Asian ideographs used in the Unicode Standard.
  • E. Unicode Technical Standard #35
    Unicode Technical Standard #35 is a Unicode Consortium specification that defines the Locale Data Markup Language (LDML) and related mechanisms for internationalization, including formatting of dates, times, numbers, and other locale-sensitive data.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Normalization Form KC
Target entity description: Normalization Form KC is a Unicode text normalization form that applies compatibility decomposition followed by canonical composition to produce a standardized representation of equivalent text.
  • A. Unicode normalization chosen
    Unicode normalization is a set of standardized processes that convert equivalent Unicode text sequences into a consistent canonical form to ensure reliable comparison, searching, and processing of text across systems.
  • B. Alphabetic Presentation Forms
    Alphabetic Presentation Forms is a Unicode block that contains compatibility characters for various alphabetic scripts, primarily providing precomposed glyph variants used in legacy text encodings and typographic contexts.
  • C. CJK Unified Ideographs Extension A
    CJK Unified Ideographs Extension A is a Unicode block that adds additional rare and historic Chinese, Japanese, and Korean characters beyond those included in the main CJK Unified Ideographs block.
  • D. Unicode Standard Annex #38
    Unicode Standard Annex #38 is a technical report that defines the Unicode Han Database (Unihan), specifying data fields and properties for East Asian ideographs used in the Unicode Standard.
  • E. Unicode Technical Standard #35
    Unicode Technical Standard #35 is a Unicode Consortium specification that defines the Locale Data Markup Language (LDML) and related mechanisms for internationalization, including formatting of dates, times, numbers, and other locale-sensitive data.
  • F. None of above.

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_69e245836014819091b91ed3074742a3 completed April 17, 2026, 2:36 p.m.
NER Named-entity recognition batch_69f1615c18f88190ad4f23639d15f337 completed April 29, 2026, 1:39 a.m.
Created at: April 17, 2026, 2:45 p.m.