Triple

T2175289
Position Surface form Disambiguated ID Type / Status
Subject DocBook E48511 entity
Predicate hasSchemaLanguage P37416 FINISHED
Object RELAX NG E24278 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: RELAX NG | Statement: [DocBook, hasSchemaLanguage, RELAX NG]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: RELAX NG
Context triple: [DocBook, hasSchemaLanguage, RELAX NG]
  • A. RELAX NG chosen
    RELAX NG is a schema language used to define and validate the structure and content of XML documents in a concise and flexible way.
  • B. Schematron
    Schematron is a rule-based XML schema language that uses XPath expressions to define and validate complex structural and business constraints in XML documents.
  • C. XML Schema
    XML Schema is a W3C standard language used to define the structure, content, and data types of XML documents.
  • D. DSSSL
    DSSSL (Document Style Semantics and Specification Language) is an ISO standard language used to define stylesheets and transformations for SGML documents, particularly in technical publishing.
  • E. SGML
    SGML (Standard Generalized Markup Language) is a standardized metalanguage for defining markup languages used to structure and describe the content of electronic documents.
  • 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_69a88aa3faa48190995b233af6525815 completed March 4, 2026, 7:40 p.m.
NER Named-entity recognition batch_69abc5af20808190902031d8c0bba376 completed March 7, 2026, 6:29 a.m.
NED1 Entity disambiguation (via context triple) batch_69ae5d9eff988190a02734bd73616cba completed March 9, 2026, 5:41 a.m.
Created at: March 4, 2026, 7:45 p.m.