Triple
T1096270
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | XML Schema |
E24277
|
entity |
| Predicate | relatedStandard |
P37
|
FINISHED |
| Object |
XPath
XPath is a query language used to navigate and select nodes in XML documents based on their structure and content.
|
E127246
|
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: XPath | Statement: [XML Schema, relatedStandard, XPath]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: XPath Context triple: [XML Schema, relatedStandard, XPath]
-
A.
XQuery
XQuery is a functional query and programming language designed for extracting and manipulating data from XML documents and related data sources.
-
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.
XML
XML (Extensible Markup Language) is a flexible, text-based markup language designed for structuring, storing, and transporting data in a platform-independent way.
-
D.
XML Namespaces
XML Namespaces is a W3C specification that provides a method for qualifying element and attribute names in XML documents to avoid naming conflicts between vocabularies.
-
E.
XHTML
XHTML is a reformulation of HTML as an XML-based markup language designed to create structured, standards-compliant web pages.
- 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: XPath Triple: [XML Schema, relatedStandard, XPath]
Generated description
XPath is a query language used to navigate and select nodes in XML documents based on their structure and content.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: XPath Target entity description: XPath is a query language used to navigate and select nodes in XML documents based on their structure and content.
-
A.
XQuery
XQuery is a functional query and programming language designed for extracting and manipulating data from XML documents and related data sources.
-
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.
XML
XML (Extensible Markup Language) is a flexible, text-based markup language designed for structuring, storing, and transporting data in a platform-independent way.
-
D.
XML Namespaces
XML Namespaces is a W3C specification that provides a method for qualifying element and attribute names in XML documents to avoid naming conflicts between vocabularies.
-
E.
XHTML
XHTML is a reformulation of HTML as an XML-based markup language designed to create structured, standards-compliant web pages.
- 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_69a4940542308190ac2a0b1f730b7cfc |
completed | March 1, 2026, 7:31 p.m. |
| NER | Named-entity recognition | batch_69a4b99ffb3481908cd168b6c58e1c6d |
completed | March 1, 2026, 10:11 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ac4c3bb31881908768a909ce56a95d |
completed | March 7, 2026, 4:03 p.m. |
| NEDg | Description generation | batch_69ac5020f5748190b89c938240e63637 |
completed | March 7, 2026, 4:19 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69ac50a982748190964d4fbef332baa5 |
completed | March 7, 2026, 4:22 p.m. |
Created at: March 1, 2026, 7:42 p.m.