Triple
T1096497
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | XQuery |
E24282
|
entity |
| Predicate | hasVersion |
P455
|
FINISHED |
| Object | XQuery 1.0 |
E24282
|
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: XQuery 1.0 | Statement: [XQuery, hasVersion, XQuery 1.0]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: XQuery 1.0 Context triple: [XQuery, hasVersion, XQuery 1.0]
-
A.
XQuery
chosen
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.
RELAX NG
RELAX NG is a schema language used to define and validate the structure and content of XML documents in a concise and flexible way.
-
D.
XML
XML (Extensible Markup Language) is a flexible, text-based markup language designed for structuring, storing, and transporting data in a platform-independent way.
-
E.
XML Schema
XML Schema is a W3C standard language used to define the structure, content, and data types of XML documents.
- 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_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. |
Created at: March 1, 2026, 7:42 p.m.