Triple

T22891470
Position Surface form Disambiguated ID Type / Status
Subject The Unicode Standard E568049 entity
Predicate primaryEncodingForms P66343 FINISHED
Object UTF-8 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: UTF-8 | Statement: [The Unicode Standard, primaryEncodingForms, UTF-8]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: UTF-8
Context triple: [The Unicode Standard, primaryEncodingForms, UTF-8]
  • A. UTF-8 chosen
    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.
  • B. UTF-16
    UTF-16 is a variable-length character encoding for Unicode that represents most common characters in one 16-bit code unit and others, including supplementary characters, in pairs of 16-bit code units.
  • C. 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.
  • D. UTF-7
    UTF-7 is an obsolete, 7-bit Unicode text encoding designed primarily for safe transmission of Unicode data over email systems that were not fully 8-bit clean.
  • E. UTF-32
    UTF-32 is a fixed-length Unicode character encoding that represents each code point using 32 bits, providing simple indexing at the cost of higher memory usage.
  • 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: primaryEncodingForms
Context triple: [The Unicode Standard, primaryEncodingForms, UTF-8]
  • A. encodingForm chosen
    Indicates the specific format or scheme used to encode information or data in a representation or communication.
  • B. encodedIn
    Indicates that one entity is represented, stored, or expressed within another entity using a specific encoding or format.
  • C. primaryModes
    Indicates the main methods, forms, or channels through which something typically operates, is expressed, or is carried out.
  • D. encodes
    Indicates that one entity contains or represents the information, instructions, or structure of another in a coded or symbolic form.
  • E. hasDistinctLetterForms
    Indicates that the related writing system or symbol set uses different visual shapes or styles for the same letter in different contexts (such as position, case, or usage).
  • 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_69e2458c23ec81908fa2570692c6614f completed April 17, 2026, 2:37 p.m.
NER Named-entity recognition batch_69f17fc59e108190a22f90c2439830fb completed April 29, 2026, 3:49 a.m.
PD Predicate disambiguation batch_69ef3b6b2e2481908258156937b5a745 completed April 27, 2026, 10:33 a.m.
Created at: April 17, 2026, 3:40 p.m.