Triple

T95415
Position Surface form Disambiguated ID Type / Status
Subject HTML E1918 entity
Predicate influenced P9 FINISHED
Object XHTML E3756 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: [HTML, influenced, XHTML]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: XHTML
Context triple: [HTML, influenced, XHTML]
  • A. XML chosen
    XML (Extensible Markup Language) is a flexible, text-based markup language designed for structuring, storing, and transporting data in a platform-independent way.
  • B. HTML
    HTML (HyperText Markup Language) is the standard markup language used to structure and present content on the World Wide Web.
  • C. DOM
    The Document Object Model (DOM) is a platform- and language-neutral interface that represents structured documents like HTML and XML as a tree of objects, enabling programs and scripts to dynamically access and update their content and structure.
  • D. HTTP
    HTTP (Hypertext Transfer Protocol) is the foundational application-layer protocol used for transmitting web pages and other resources across the World Wide Web.
  • E. 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.
  • 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_69a24d4862f881908cc8b89d3a78031d completed Feb. 28, 2026, 2:04 a.m.
NER Named-entity recognition batch_69a24fd4777c81909ea9b9a6bd4f7ad5 completed Feb. 28, 2026, 2:15 a.m.
NED1 Entity disambiguation (via context triple) batch_69a266ed314881908b6e5e7a91930b56 completed Feb. 28, 2026, 3:54 a.m.
Created at: Feb. 28, 2026, 2:09 a.m.