Triple

T192806
Position Surface form Disambiguated ID Type / Status
Subject XML E3756 entity
Predicate inspiredBy P9 FINISHED
Object SGML E8666 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: SGML | Statement: [XML, inspiredBy, SGML]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: SGML
Context triple: [XML, inspiredBy, SGML]
  • A. SGML chosen
    SGML (Standard Generalized Markup Language) is a standardized metalanguage for defining markup languages used to structure and describe the content of electronic documents.
  • B. XML
    XML (Extensible Markup Language) is a flexible, text-based markup language designed for structuring, storing, and transporting data in a platform-independent way.
  • C. RELAX NG
    RELAX NG is a schema language used to define and validate the structure and content of XML documents in a concise and flexible way.
  • D. SVG
    SVG (Scalable Vector Graphics) is an XML-based vector image format for two-dimensional graphics that supports interactivity and animation, widely used for web graphics due to its scalability and resolution independence.
  • E. XSLT
    XSLT is a language for transforming XML documents into other formats such as XML, HTML, or plain text using template-based rules.
  • 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_69a2548debd48190ae3a06d6e65b53c6 completed Feb. 28, 2026, 2:35 a.m.
NER Named-entity recognition batch_69a259669ba08190a5be1d2e10e70b27 completed Feb. 28, 2026, 2:56 a.m.
NED1 Entity disambiguation (via context triple) batch_69a3115a91148190b554ca5fe372569c completed Feb. 28, 2026, 4:01 p.m.
Created at: Feb. 28, 2026, 2:41 a.m.