Triple

T14870364
Position Surface form Disambiguated ID Type / Status
Subject tso E349726 entity
Predicate usedInStandard P1587 FINISHED
Object BCP 47 E682197 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: BCP 47 | Statement: [tso, usedInStandard, BCP 47]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: BCP 47
Context triple: [tso, usedInStandard, BCP 47]
  • A. IETF BCP 47 chosen
    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.
  • B. ISO 639
    ISO 639 is an international standard that defines codes for the representation of names of languages.
  • C. 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.
  • D. IANA language subtag registry
    The IANA language subtag registry is the official database maintained by the Internet Assigned Numbers Authority that defines standardized language, script, region, and variant subtags used in BCP 47 language tags for internet and software localization.
  • E. 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.
  • 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_69d822ee4f408190b6ac3b2fa434f0df completed April 9, 2026, 10:06 p.m.
NER Named-entity recognition batch_69ded57967748190a7c05ebb74aacb7c completed April 15, 2026, 12:02 a.m.
NED1 Entity disambiguation (via context triple) batch_69fe651067cc8190b9c218ef1f802762 completed May 8, 2026, 10:34 p.m.
Created at: April 10, 2026, 1:55 a.m.