Triple

T16747900
Position Surface form Disambiguated ID Type / Status
Subject ISO 15706 E407001 entity
Predicate relatedStandard P37 FINISHED
Object ISO 639 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 | Statement: [ISO 15706, relatedStandard, ISO 639]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: ISO 639
Context triple: [ISO 15706, relatedStandard, ISO 639]
  • A. ISO 639 chosen
    ISO 639 is an international standard that defines codes for the representation of names of languages.
  • B. ISO 639-3
    ISO 639-3 is an international standard that assigns three-letter codes to uniquely identify the world’s languages, including many lesser-known and endangered ones.
  • C. 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.
  • D. ISO 15924
    ISO 15924 is an international standard that assigns four-letter codes to the world’s writing systems and scripts for use in information processing and interchange.
  • E. 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.
  • 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_69d8838ffb088190a0b11149929006bf completed April 10, 2026, 4:58 a.m.
NER Named-entity recognition batch_69e3aa2439848190a86a5bfc0702e2fe completed April 18, 2026, 3:58 p.m.
NED1 Entity disambiguation (via context triple) batch_6a00a522255c8190ab16d7ad233fcd3b completed May 10, 2026, 3:32 p.m.
Created at: April 10, 2026, 5:21 a.m.