Triple

T723691
Position Surface form Disambiguated ID Type / Status
Subject XNYS E14673 entity
Predicate hasStandard P1371 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: [XNYS, hasStandard, ISO 10383]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: ISO 10383
Context triple: [XNYS, hasStandard, 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 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.
  • C. ISO 3297
    ISO 3297 is the international standard that defines the structure, assignment, and use of the International Standard Serial Number (ISSN) for identifying serial publications.
  • D. ISO 7775
    ISO 7775 is an older international standard that defined message formats for securities transactions and related financial communications, later superseded by ISO 15022.
  • E. ISO/IEC 8652
    ISO/IEC 8652 is the international standard that formally defines the Ada programming language, including its syntax, semantics, and core features.
  • 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_69a4934c753c81909b309027e48b9b3a completed March 1, 2026, 7:28 p.m.
NER Named-entity recognition batch_69a4a5a5360c8190b16e1e4f4206d0aa completed March 1, 2026, 8:46 p.m.
NED1 Entity disambiguation (via context triple) batch_69a64a5a7e788190b5ad2505b68ca48d completed March 3, 2026, 2:41 a.m.
Created at: March 1, 2026, 7:37 p.m.