Triple

T3420080
Position Surface form Disambiguated ID Type / Status
Subject WebKit E72094 entity
Predicate supportsStandard P1587 FINISHED
Object HTML5 E13761 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: HTML5 | Statement: [WebKit, supportsStandard, HTML5]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: HTML5
Context triple: [WebKit, supportsStandard, HTML5]
  • A. HTML5 chosen
    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.
  • B. HTML
    HTML (HyperText Markup Language) is the standard markup language used to structure and present content on the World Wide Web.
  • C. HTML Living Standard
    The HTML Living Standard is the continuously updated, authoritative specification for the HTML language maintained by the WHATWG to define how web content is structured and behaves across browsers.
  • D. DHTML
    DHTML (Dynamic HTML) is a web development technique that combines HTML, CSS, and JavaScript to create interactive and animated web pages that update content dynamically without reloading.
  • E. HTM
    HTM is the public transport company that operates trams and buses in and around The Hague in the Netherlands.
  • 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_69ad85ad38e48190b7660c5118a35289 completed March 8, 2026, 2:20 p.m.
NER Named-entity recognition batch_69adb94eb9e8819087a525df4550914b completed March 8, 2026, 6 p.m.
NED1 Entity disambiguation (via context triple) batch_69b354701e908190a8a7f14ae578fa5d completed March 13, 2026, 12:04 a.m.
Created at: March 8, 2026, 3:15 p.m.