Triple
T10329013
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Web IDL Standard |
E242830
|
entity |
| Predicate | relatedTo |
P37
|
FINISHED |
| Object | HTML Standard |
E49493
|
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 Standard | Statement: [Web IDL Standard, relatedTo, HTML Standard]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: HTML Standard Context triple: [Web IDL Standard, relatedTo, HTML Standard]
-
A.
HTML Living Standard
chosen
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.
-
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.
HTML
HTML (HyperText Markup Language) is the standard markup language used to structure and present content on the World Wide Web.
-
D.
XHTML
XHTML is a reformulation of HTML as an XML-based markup language designed to create structured, standards-compliant web pages.
-
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_69d381af787481908bc401325c760a88 |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d4d7cfd54c8190b6f88598339536d1 |
completed | April 7, 2026, 10:09 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d71db4a8dc81909adb2a044e74fd6b |
completed | April 9, 2026, 3:32 a.m. |
Created at: April 6, 2026, 11:52 a.m.