Triple

T8798605
Position Surface form Disambiguated ID Type / Status
Subject nan E209346 entity
Predicate partOf P40 FINISHED
Object ISO 639 language code set E18761 NE 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: ISO 639 language code set | Statement: [nan, partOf, ISO 639 language code set]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: ISO 639 language code set
Context triple: [nan, partOf, ISO 639 language code set]
  • A. ISO 639 chosen
    ISO 639 is an international standard that defines codes for the representation of names of languages.
  • B. ISO 639-3 Registration Authority
    The ISO 639-3 Registration Authority is the organization responsible for maintaining and updating the ISO 639-3 standard, which assigns three-letter codes to the world’s languages.
  • C. SSH Language Tags
    SSH Language Tags are standardized identifiers used within the SSH protocol to specify human languages for messages and data, enabling proper localization and internationalization.
  • D. IETF BCP 47
    IETF BCP 47 is the Internet standard that defines the structure and use of language tags for identifying human languages and related variants in digital systems.
  • E. ISO 3166-1
    ISO 3166-1 is an international standard published by ISO that defines globally recognized country codes in alpha-2, alpha-3, and numeric formats.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

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_69ca836240888190a62b262e56a69d2f completed March 30, 2026, 2:06 p.m.
NER Named-entity recognition batch_69cc5fa50dd081908fa5e4ffa70342e2 completed March 31, 2026, 11:58 p.m.
NED1 Entity disambiguation (via context triple) batch_69cf6f658f248190957eba821b07cc4f completed April 3, 2026, 7:42 a.m.
Created at: March 30, 2026, 6:44 p.m.