Triple
T192894
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | SVG |
E3757
|
entity |
| Predicate | compatibleWith |
P203
|
FINISHED |
| Object |
XHTML
XHTML is a reformulation of HTML as an XML-based markup language designed to create structured, standards-compliant web pages.
|
E24914
|
NE FINISHED |
How this triple was built (4 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: XHTML | Statement: [SVG, compatibleWith, XHTML]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: XHTML Context triple: [SVG, compatibleWith, XHTML]
-
A.
XML
XML (Extensible Markup Language) is a flexible, text-based markup language designed for structuring, storing, and transporting data in a platform-independent way.
-
B.
XSLT
XSLT is a language for transforming XML documents into other formats such as XML, HTML, or plain text using template-based rules.
-
C.
HTML
HTML (HyperText Markup Language) is the standard markup language used to structure and present content on the World Wide Web.
-
D.
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.
-
E.
SGML
SGML (Standard Generalized Markup Language) is a standardized metalanguage for defining markup languages used to structure and describe the content of electronic documents.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: XHTML Triple: [SVG, compatibleWith, XHTML]
Generated description
XHTML is a reformulation of HTML as an XML-based markup language designed to create structured, standards-compliant web pages.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: XHTML Target entity description: XHTML is a reformulation of HTML as an XML-based markup language designed to create structured, standards-compliant web pages.
-
A.
XML
XML (Extensible Markup Language) is a flexible, text-based markup language designed for structuring, storing, and transporting data in a platform-independent way.
-
B.
XSLT
XSLT is a language for transforming XML documents into other formats such as XML, HTML, or plain text using template-based rules.
-
C.
HTML
HTML (HyperText Markup Language) is the standard markup language used to structure and present content on the World Wide Web.
-
D.
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.
-
E.
SGML
SGML (Standard Generalized Markup Language) is a standardized metalanguage for defining markup languages used to structure and describe the content of electronic documents.
- F. None of above. chosen
Provenance (5 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_69a2548debd48190ae3a06d6e65b53c6 |
completed | Feb. 28, 2026, 2:35 a.m. |
| NER | Named-entity recognition | batch_69a259669ba08190a5be1d2e10e70b27 |
completed | Feb. 28, 2026, 2:56 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a3161cdc4c8190bc67683a1a5d39d9 |
completed | Feb. 28, 2026, 4:21 p.m. |
| NEDg | Description generation | batch_69a31677d5c48190967cacd20fd6357a |
completed | Feb. 28, 2026, 4:23 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69a316d53594819095710388c11624eb |
completed | Feb. 28, 2026, 4:24 p.m. |
Created at: Feb. 28, 2026, 2:41 a.m.