Triple

T18563530
Position Surface form Disambiguated ID Type / Status
Subject Unicode Technical Reports E453704 entity
Predicate includesExample P1259 FINISHED
Object Unicode Emoji technical report — 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 Emoji technical report | Statement: [Unicode Technical Reports, includesExample, Unicode Emoji technical report]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Unicode Emoji technical report
Context triple: [Unicode Technical Reports, includesExample, Unicode Emoji technical report]
  • A. 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.
  • B. Unicode Technical Reports chosen
    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.
  • C. 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.
  • D. 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.
  • E. 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.
  • 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_69d8d38974308190a9174430ef256b73 completed April 10, 2026, 10:40 a.m.
NER Named-entity recognition batch_69e53afc57448190abd90167d7e12a18 completed April 19, 2026, 8:28 p.m.
Created at: April 10, 2026, 11:42 a.m.