Triple

T22443657
Position Surface form Disambiguated ID Type / Status
Subject Electron E554815 entity
Predicate usesTechnology P1485 FINISHED
Object HTML NE NERFINISHED

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 | Statement: [Electron, usesTechnology, HTML]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: HTML
Context triple: [Electron, usesTechnology, HTML]
  • A. HTML chosen
    HTML (HyperText Markup Language) is the standard markup language used to structure and present content on the World Wide Web.
  • B. 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.
  • C. HTM
    HTM is the public transport company that operates trams and buses in and around The Hague in the Netherlands.
  • D. HTMP
    HTMP is the ICAO airport code assigned to Mpanda Airport in Tanzania.
  • E. 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.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69e11e5010e48190ae1e9c9db9697637 completed April 16, 2026, 5:37 p.m.
NER Named-entity recognition batch_69f15ae40f9081908674015beb33f74e completed April 29, 2026, 1:12 a.m.
Created at: April 16, 2026, 8:47 p.m.