Triple

T5261590
Position Surface form Disambiguated ID Type / Status
Subject ISO 6166 E118835 entity
Predicate relatedStandard P37 FINISHED
Object ISO 10383 E86738 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 10383 | Statement: [ISO 6166, relatedStandard, ISO 10383]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: ISO 10383
Context triple: [ISO 6166, relatedStandard, ISO 10383]
  • A. ISO 10383 chosen
    ISO 10383 is an international standard that defines and maintains Market Identifier Codes (MICs) used to uniquely identify securities trading venues and related entities worldwide.
  • B. ISO 10957
    ISO 10957 is the international standard that defines the International Standard Music Number (ISMN) system used to uniquely identify printed music publications worldwide.
  • C. ISO 10589
    ISO 10589 is the international standard that defines the Intermediate System to Intermediate System (IS-IS) routing protocol used for exchanging routing information within an autonomous system.
  • D. ISO 2108
    ISO 2108 is the international standard that defines the structure and use of the International Standard Book Number (ISBN) system for identifying books and related publications.
  • E. ISO 843
    ISO 843 is the international standard that defines how to systematically transliterate Modern Greek characters into Latin script.
  • 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_69bd446a42c88190b7ecbef006561d55 completed March 20, 2026, 12:58 p.m.
NER Named-entity recognition batch_69bd7bd0c5f48190a1be89314c59f96b completed March 20, 2026, 4:54 p.m.
NED1 Entity disambiguation (via context triple) batch_69befe85a3f88190ae014b18b1df202e completed March 21, 2026, 8:24 p.m.
Created at: March 20, 2026, 1:50 p.m.