Triple
T5767539
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | XPath 3.0 |
E127250
|
entity |
| Predicate | usedWith |
P4791
|
FINISHED |
| Object | XSLT 3.0 |
E24281
|
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: XSLT 3.0 | Statement: [XPath 3.0, usedWith, XSLT 3.0]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: XSLT 3.0 Context triple: [XPath 3.0, usedWith, XSLT 3.0]
-
A.
XPath 3.0
XPath 3.0 is a version of the XML Path Language that extends earlier XPath standards with richer expressions, functions, and data types for querying and transforming XML and related data.
-
B.
XSLT
chosen
XSLT is a language for transforming XML documents into other formats such as XML, HTML, or plain text using template-based rules.
-
C.
XQuery
XQuery is a functional query and programming language designed for extracting and manipulating data from XML documents and related data sources.
-
D.
XPath 2.0
XPath 2.0 is an enhanced version of the XML path language that adds richer data types, functions, and expression capabilities for querying and manipulating XML documents.
-
E.
XQuery Scripting Extension
XQuery Scripting Extension is an enhancement to the XQuery language that adds scripting capabilities such as variables, loops, and side-effecting operations to support more procedural and application-oriented use cases.
- 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_69c00834f6308190851b0abeddd8ed7e |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c029731adc8190888adc8178a08e90 |
completed | March 22, 2026, 5:40 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c07e5d8c8c819081067de808ac1b56 |
completed | March 22, 2026, 11:42 p.m. |
Created at: March 22, 2026, 3:49 p.m.