Triple

T12084295
Position Surface form Disambiguated ID Type / Status
Subject Nokia 2700 classic E287765 entity
Predicate supportsBrowser P5090 FINISHED
Object HTML 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 | Statement: [Nokia 2700 classic, supportsBrowser, HTML]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: HTML
Context triple: [Nokia 2700 classic, supportsBrowser, 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 (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_69d6ab4964708190850585628b287b0c completed April 8, 2026, 7:23 p.m.
NER Named-entity recognition batch_69d91513bbb0819084a8bb877e03060c completed April 10, 2026, 3:19 p.m.
NED1 Entity disambiguation (via context triple) batch_69f5f666bf1c819089de1235617e775b completed May 2, 2026, 1:04 p.m.
Created at: April 8, 2026, 9:48 p.m.