Triple

T380480
Position Surface form Disambiguated ID Type / Status
Subject SGML E8666 entity
Predicate influenced P9 FINISHED
Object XHTML E24914 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: XHTML | Statement: [SGML, influenced, XHTML]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: XHTML
Context triple: [SGML, influenced, XHTML]
  • A. XHTML chosen
    XHTML is a reformulation of HTML as an XML-based markup language designed to create structured, standards-compliant web pages.
  • 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. XSLT
    XSLT is a language for transforming XML documents into other formats such as XML, HTML, or plain text using template-based rules.
  • D. HTML
    HTML (HyperText Markup Language) is the standard markup language used to structure and present content on the World Wide Web.
  • E. HTML5
    HTML5 is the fifth major version of the HyperText Markup Language standard, introducing modern web features such as semantic elements, native audio and video, and enhanced APIs for building rich, interactive web applications.
  • 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_69a2e7f47dd08190a4e294ccbbe46cd4 completed Feb. 28, 2026, 1:04 p.m.
NER Named-entity recognition batch_69a2ec2c95088190a603bb1ee076ebd6 completed Feb. 28, 2026, 1:22 p.m.
NED1 Entity disambiguation (via context triple) batch_69a3faffa5848190b77503516f3d0ba6 completed March 1, 2026, 8:38 a.m.
Created at: Feb. 28, 2026, 1:08 p.m.