Triple

T6991526
Position Surface form Disambiguated ID Type / Status
Subject UTF-8 E162096 entity
Predicate designedFor P98 FINISHED
Object Unicode 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 | Statement: [UTF-8, designedFor, Unicode]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Unicode
Context triple: [UTF-8, designedFor, 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 Standard
    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 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.
  • D. 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.
  • E. 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.
  • 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_69c68856d7808190ab33ee914640281b completed March 27, 2026, 1:38 p.m.
NER Named-entity recognition batch_69c6dbc1f63c8190837cfd71cf5ed613 completed March 27, 2026, 7:34 p.m.
NED1 Entity disambiguation (via context triple) batch_69c761d6ed5481909ccf1650fe6dc747 completed March 28, 2026, 5:06 a.m.
Created at: March 27, 2026, 2:32 p.m.