Triple

T14391098
Position Surface form Disambiguated ID Type / Status
Subject Székelys E356842 entity
Predicate ISO639Language P114062 FINISHED
Object hu 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: hu | Statement: [Székelys, ISO639Language, hu]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: ISO639Language
Context triple: [Székelys, ISO639Language, hu]
  • A. ISO639Scope
    Indicates the classification of a language according to its scope, such as whether it represents an individual language, a macrolanguage, or a collection of languages.
  • B. ISO639Macrolanguage
    Indicates that a language variety is part of a broader ISO 639-defined macrolanguage grouping that encompasses multiple closely related individual languages.
  • C. ISO639-3CodeOfLanguage
    Indicates that one entity is the ISO 639-3 three-letter language code assigned to the language represented by the other entity.
  • D. ISO639CollectiveCode
    Indicates that the relationship assigns or associates an ISO 639 collective language code (a code representing a group of related languages) to the relevant language entity or set of languages.
  • E. ISO639-6Code
    Indicates the standardized ISO 639-6 four-letter code that uniquely identifies a specific language variety or dialect.
  • F. None of above. chosen

Provenance (4 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_69d827927c988190ad98bb0360981783 completed April 9, 2026, 10:26 p.m.
NER Named-entity recognition batch_69de902b9acc8190817ffa848a76a880 completed April 14, 2026, 7:06 p.m.
PD Predicate disambiguation batch_69de2aa024c48190805df6a9d63deb10 completed April 14, 2026, 11:53 a.m.
PDg Predicate description generation batch_69de2e08b6c08190bb4c929deab236a6 completed April 14, 2026, 12:07 p.m.
Created at: April 10, 2026, 1:16 a.m.