Triple

T21718418
Position Surface form Disambiguated ID Type / Status
Subject Unicode 6.1 E536089 entity
Predicate hasTechnicalReport P5712 FINISHED
Object Unicode Standard Annex #9 (Bidirectional Algorithm, updated for 6.1) 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 Standard Annex #9 (Bidirectional Algorithm, updated for 6.1) | Statement: [Unicode 6.1, hasTechnicalReport, Unicode Standard Annex #9 (Bidirectional Algorithm, updated for 6.1)]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Unicode Standard Annex #9 (Bidirectional Algorithm, updated for 6.1)
Context triple: [Unicode 6.1, hasTechnicalReport, Unicode Standard Annex #9 (Bidirectional Algorithm, updated for 6.1)]
  • A. Unicode bidirectional algorithm chosen
    The Unicode bidirectional algorithm is a core text-processing method that determines the correct display order of mixed left-to-right and right-to-left scripts, such as Latin and Arabic, in digital text.
  • B. 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.
  • C. 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.
  • 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 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 (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_69e0c46c6dd88190a595375fa6ebd701 completed April 16, 2026, 11:13 a.m.
NER Named-entity recognition batch_69efd96cc58081908dda09819041b888 completed April 27, 2026, 9:47 p.m.
Created at: April 16, 2026, 6:47 p.m.