Triple

T7420518
Position Surface form Disambiguated ID Type / Status
Subject HoTMetaL E171234 entity
Predicate supportsStandard P1587 FINISHED
Object HTML 4.0 E1918 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: HTML 4.0 | Statement: [HoTMetaL, supportsStandard, HTML 4.0]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: HTML 4.0
Context triple: [HoTMetaL, supportsStandard, HTML 4.0]
  • A. HTM
    HTM is the public transport company that operates trams and buses in and around The Hague in the Netherlands.
  • B. HAL (Hypertext Application Language)
    HAL (Hypertext Application Language) is a simple, JSON-based hypermedia format that standardizes how to represent and navigate links and embedded resources in RESTful APIs.
  • C. 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.
  • D. SGML
    SGML (Standard Generalized Markup Language) is a standardized metalanguage for defining markup languages used to structure and describe the content of electronic documents.
  • E. HTML chosen
    HTML (HyperText Markup Language) is the standard markup language used to structure and present content on the World Wide Web.
  • 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_69c68a625d048190af70eb8b63bec5a0 completed March 27, 2026, 1:47 p.m.
NER Named-entity recognition batch_69c6f2ea61248190886e8e55b42ba5f1 completed March 27, 2026, 9:13 p.m.
NED1 Entity disambiguation (via context triple) batch_69c81ef7fc808190a564ab4d9d97ab37 completed March 28, 2026, 6:33 p.m.
Created at: March 27, 2026, 3:11 p.m.