Triple

T18567503
Position Surface form Disambiguated ID Type / Status
Subject Punycode E453792 entity
Predicate outputCharacterSet P7661 FINISHED
Object ASCII NE NERFINISHED

How this triple was built (3 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: ASCII | Statement: [Punycode, outputCharacterSet, ASCII]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: ASCII
Context triple: [Punycode, outputCharacterSet, ASCII]
  • A. ASCII chosen
    ASCII is a widely used character encoding standard that represents text in computers and other devices using 7-bit numerical codes for letters, digits, punctuation, and control characters.
  • B. ISO 646
    ISO 646 is an international standard for 7-bit character encodings that defines a set of basic Latin characters and allows national variants, serving as a foundation for many early computer character sets.
  • C. ASCI
    ASCI is a prestigious U.S. honor society of physician-scientists dedicated to advancing clinical and translational research.
  • D. 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.
  • E. Unicode
    Unicode is a universal character encoding standard that assigns unique code points to virtually all written scripts, symbols, and emojis used in modern computing.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: outputCharacterSet
Context triple: [Punycode, outputCharacterSet, ASCII]
  • A. usesCharacterSet chosen
    Indicates that one entity employs or relies on a specific character set defined by another entity for encoding or representing text.
  • B. characterSetType
    Indicates the type or category of character set associated with or used by an entity.
  • C. characterSetOrigin
    Indicates the source or defining system from which a particular character set is derived or specified.
  • D. perceivedAsByCharacters
    Indicates how something is viewed, interpreted, or understood by one or more characters.
  • E. codingSystemType
    Indicates the classification or category of coding system used to encode or represent information in a given context.
  • F. None of above.

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_69d8d38974308190a9174430ef256b73 completed April 10, 2026, 10:40 a.m.
NER Named-entity recognition batch_69e53affc3e08190b4d16b5ccb0bddbc completed April 19, 2026, 8:28 p.m.
PD Predicate disambiguation batch_69e478c16e0c8190b03966aa23c395a6 completed April 19, 2026, 6:40 a.m.
Created at: April 10, 2026, 11:43 a.m.