Triple

T6398347
Position Surface form Disambiguated ID Type / Status
Subject UTR #29 E143995 entity
Predicate category P87 FINISHED
Object Unicode Technical Report on text processing E26869 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 Technical Report on text processing | Statement: [UTR #29, category, Unicode Technical Report on text processing]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Unicode Technical Report on text processing
Context triple: [UTR #29, category, Unicode Technical Report on text processing]
  • A. Unicode Technical Reports
    Unicode Technical Reports are supplementary documents published by the Unicode Consortium that provide detailed guidance, algorithms, and clarifications on specific aspects of Unicode beyond what is covered in the core specification.
  • B. Unicode text processing algorithms
    Unicode text processing algorithms are standardized procedures that define how Unicode text is compared, sorted, segmented, normalized, and otherwise manipulated consistently across different systems and languages.
  • C. Unicode Technical Report #29 chosen
    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.
  • D. The 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 written language worldwide.
  • 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 (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_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.
Created at: March 22, 2026, 4:35 p.m.