Triple

T188996
Position Surface form Disambiguated ID Type / Status
Subject Basic Latin E3675 entity
Predicate introducedInStandard P5655 FINISHED
Object Unicode 1.0 E3674 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: Unicode 1.0 | Statement: [Basic Latin, introducedInStandard, Unicode 1.0]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Unicode 1.0
Context triple: [Basic Latin, introducedInStandard, Unicode 1.0]
  • A. 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.
  • B. 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.
  • C. ISO/IEC 10646
    ISO/IEC 10646 is an international standard that defines the Universal Coded Character Set (UCS), a comprehensive repertoire of characters used worldwide and closely aligned with the Unicode Standard.
  • D. 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.
  • E. Unicode Technical Report #29
    Unicode Technical Report #29 is the specification that defines how to determine and segment user-perceived text elements (grapheme clusters), words, and sentences in Unicode text.
  • 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_69a2548debd48190ae3a06d6e65b53c6 completed Feb. 28, 2026, 2:35 a.m.
NER Named-entity recognition batch_69a25bc834388190a93ec1ab0d5946de completed Feb. 28, 2026, 3:06 a.m.
NED1 Entity disambiguation (via context triple) batch_69a33e3bf8948190a30af36f4c21eded completed Feb. 28, 2026, 7:13 p.m.
Created at: Feb. 28, 2026, 2:41 a.m.