Triple

T9898905
Position Surface form Disambiguated ID Type / Status
Subject Active Server Pages E182238 entity
Predicate supportsOutputFormat P23634 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: [Active Server Pages, supportsOutputFormat, HTML]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: HTML
Context triple: [Active Server Pages, supportsOutputFormat, 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_69ca82876f8081909cf75df0f99bb13f completed March 30, 2026, 2:02 p.m.
NER Named-entity recognition batch_69cdb4adc03481909e0f657db01e5bab completed April 2, 2026, 12:13 a.m.
NED1 Entity disambiguation (via context triple) batch_69d1eb1b9534819093c5150f1ed8f685 completed April 5, 2026, 4:54 a.m.
Created at: March 30, 2026, 8:40 p.m.