Triple

T13429256
Position Surface form Disambiguated ID Type / Status
Subject 15 WG E313563 entity
Predicate primaryCommandLanguage P6537 FINISHED
Object English LITERAL FINISHED

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: English | Statement: [15 WG, primaryCommandLanguage, English]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: primaryCommandLanguage
Context triple: [15 WG, primaryCommandLanguage, English]
  • A. languageOfCommand chosen
    Indicates that a specified language is the one in which a given command is expressed or issued.
  • B. primaryLanguageType
    Indicates the main category or kind of language (such as spoken, written, or signed) that serves as the primary mode of communication in a given context or for a given entity.
  • C. primaryLanguageOf
    Indicates that a specified language is the main or official language used by a particular entity (such as a person, organization, or region).
  • D. primaryLanguageIn
    Indicates that a specified language is the main or official language used within a particular place, organization, or context.
  • E. primaryLanguageBinding
    Indicates that one language or language-specific implementation is designated as the main or default binding for a given resource, interface, or functionality.
  • 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_69d806ad0c44819088833ae1ec9e9690 completed April 9, 2026, 8:06 p.m.
NER Named-entity recognition batch_69dbaed304ac8190a8021f749de8164c completed April 12, 2026, 2:40 p.m.
PD Predicate disambiguation batch_69d9a03926188190ab3948d1f5d3941f completed April 11, 2026, 1:13 a.m.
Created at: April 9, 2026, 9:40 p.m.