Triple

T17154088
Position Surface form Disambiguated ID Type / Status
Subject Saho language E416296 entity
Predicate hasISOStandard P1587 FINISHED
Object ISO 639-2 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 639-2 | Statement: [Saho language, hasISOStandard, ISO 639-2]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: ISO 639-2
Context triple: [Saho language, hasISOStandard, ISO 639-2]
  • 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 3166-3
    ISO 3166-3 is the part of the ISO 3166 standard that defines codes for countries and territories that have been removed from the current ISO 3166-1 list, providing their former country codes and their replacements.
  • E. 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.
  • 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_69d886d279c081909f8ff1f743ddeb69 completed April 10, 2026, 5:12 a.m.
NER Named-entity recognition batch_69e3f4092c40819096359ff90af16c3e completed April 18, 2026, 9:13 p.m.
NED1 Entity disambiguation (via context triple) batch_6a0148337a348190b8739eb3f553f1d9 completed May 11, 2026, 3:08 a.m.
Created at: April 10, 2026, 5:37 a.m.