Triple

T95462
Position Surface form Disambiguated ID Type / Status
Subject W3C Recommendation E1919 entity
Predicate hasExample P1259 FINISHED
Object SVG Recommendation E3757 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: SVG Recommendation | Statement: [W3C Recommendation, hasExample, SVG Recommendation]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: SVG Recommendation
Context triple: [W3C Recommendation, hasExample, SVG Recommendation]
  • A. SVG chosen
    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.
  • B. W3C Recommendation
    A W3C Recommendation is a mature, stable web standard published by the World Wide Web Consortium to promote interoperability and best practices across the World Wide Web.
  • C. WCAG
    WCAG (Web Content Accessibility Guidelines) is an internationally recognized set of guidelines that define how to make web content more accessible to people with disabilities.
  • D. HTML
    HTML (HyperText Markup Language) is the standard markup language used to structure and present content on the World Wide Web.
  • E. Tableau
    Tableau is a widely used data visualization and business intelligence software platform that enables users to analyze, explore, and present data through interactive dashboards and reports.
  • 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.