Triple

T6398641
Position Surface form Disambiguated ID Type / Status
Subject Telu E144002 entity
Predicate encodingContext P5020 FINISHED
Object Unicode E3674 NE FINISHED

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: Unicode | Statement: [Telu, encodingContext, Unicode]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Unicode
Context triple: [Telu, encodingContext, Unicode]
  • A. Unicode chosen
    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 Character Database
    The Unicode Character Database is a comprehensive collection of machine-readable data files that define the properties, classifications, and behaviors of every character encoded in the Unicode Standard.
  • 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. UTF-8
    UTF-8 is a widely used variable-length character encoding standard for Unicode that efficiently represents text in most of the world's writing systems while maintaining backward compatibility with ASCII.
  • E. CJK Unified Ideographs
    CJK Unified Ideographs is a standardized set of Chinese, Japanese, and Korean logographic characters encoded in Unicode to unify and represent Han-based writing systems across East Asia.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: encodingContext
Context triple: [Telu, encodingContext, Unicode]
  • A. encodingScope
    Indicates the range or extent of content or information that is covered, represented, or captured by a particular encoding.
  • B. encodingStructure
    Indicates the structural scheme or format used to encode information or data.
  • C. codingSystemContext chosen
    Indicates the coding system or classification framework within which a given code, identifier, or value is defined and interpreted.
  • D. encodedIn
    Indicates that one entity is represented, stored, or expressed within another entity using a specific encoding or format.
  • E. conversionContext
    Indicates the situational or environmental factors under which a conversion (e.g., change of state, format, or belief) occurs or is interpreted.
  • F. None of above.

Provenance (4 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_69c008dc56fc81908d43ffcc11d73bdd completed March 22, 2026, 3:21 p.m.
NER Named-entity recognition batch_69c06897ebc48190842d48cce469eba5 completed March 22, 2026, 10:09 p.m.
NED1 Entity disambiguation (via context triple) batch_69c6389bd9f48190af9811cf8cee124e completed March 27, 2026, 7:58 a.m.
PD Predicate disambiguation batch_69c060f25c088190b433f78553ff1d84 completed March 22, 2026, 9:36 p.m.
Created at: March 22, 2026, 4:35 p.m.