Triple

T22585137
Position Surface form Disambiguated ID Type / Status
Subject Unicode text processing algorithms E564767 entity
Predicate includesAlgorithm P125667 FINISHED
Object Unicode Bidirectional Algorithm — 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 Bidirectional Algorithm | Statement: [Unicode text processing algorithms, includesAlgorithm, Unicode Bidirectional Algorithm]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Unicode Bidirectional Algorithm
Context triple: [Unicode text processing algorithms, includesAlgorithm, Unicode Bidirectional Algorithm]
  • 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. 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 Line Breaking Algorithm
    The Unicode Line Breaking Algorithm is a standard specification that defines how to determine valid line break opportunities in text encoded with Unicode, ensuring consistent and readable text layout across different systems and languages.
  • 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 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 (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_69e245836014819091b91ed3074742a3 completed April 17, 2026, 2:36 p.m.
NER Named-entity recognition batch_69f1615c18f88190ad4f23639d15f337 completed April 29, 2026, 1:39 a.m.
Created at: April 17, 2026, 2:45 p.m.