Triple

T1933021
Position Surface form Disambiguated ID Type / Status
Subject IBM WebSphere DataPower E40987 entity
Predicate supportsStandard P1587 FINISHED
Object XPath E127246 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: XPath | Statement: [IBM WebSphere DataPower, supportsStandard, XPath]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: XPath
Context triple: [IBM WebSphere DataPower, supportsStandard, XPath]
  • A. XPath chosen
    XPath is a query language used to navigate and select nodes in XML documents based on their structure and content.
  • B. 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.
  • C. XQuery
    XQuery is a functional query and programming language designed for extracting and manipulating data from XML documents and related data sources.
  • D. XSLT
    XSLT is a language for transforming XML documents into other formats such as XML, HTML, or plain text using template-based rules.
  • E. 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.
  • 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_69a8864711648190b07bed24ed76258e completed March 4, 2026, 7:21 p.m.
NER Named-entity recognition batch_69abb299f3c48190a5021d320ded4405 completed March 7, 2026, 5:07 a.m.
NED1 Entity disambiguation (via context triple) batch_69adf3f16d0c8190967862b68e6cc373 completed March 8, 2026, 10:10 p.m.
Created at: March 4, 2026, 7:35 p.m.