Triple

T22481668
Position Surface form Disambiguated ID Type / Status
Subject Unicode 5.0 E555779 entity
Predicate defines P264 FINISHED
Object Unicode encoding model NE NERFINISHED

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: Unicode encoding model | Statement: [Unicode 5.0, defines, Unicode encoding model]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Unicode encoding model
Context triple: [Unicode 5.0, defines, Unicode encoding model]
  • A. Unicode
    Unicode is a universal character encoding standard that assigns unique code points to virtually all written scripts, symbols, and emojis used in modern computing.
  • B. Unicode Standard chosen
    The Unicode Standard is a universal character encoding system that assigns unique code points to text and symbols from virtually all writing systems, enabling consistent digital representation and interchange of text worldwide.
  • C. Unicode Consortium
    The Unicode Consortium is a non-profit organization that standardizes the representation of text and symbols in digital systems worldwide through the Unicode Standard.
  • D. 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.
  • E. Unicode Technical Standard #10
    Unicode Technical Standard #10 is the specification that defines the Unicode Collation Algorithm, providing a standardized method for comparing and sorting Unicode text across languages and platforms.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

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_69e11e53897c819088863779f8c50bb0 completed April 16, 2026, 5:37 p.m.
NER Named-entity recognition batch_69f15c397b248190b36c2fbfa6489693 completed April 29, 2026, 1:17 a.m.
Created at: April 16, 2026, 8:49 p.m.