Triple

T5767560
Position Surface form Disambiguated ID Type / Status
Subject XPath 3.0 E127250 entity
Predicate hasDataModel P535 FINISHED
Object XDM 3.0 E127254 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: XDM 3.0 | Statement: [XPath 3.0, hasDataModel, XDM 3.0]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: XDM 3.0
Context triple: [XPath 3.0, hasDataModel, XDM 3.0]
  • A. XDM (XQuery and XPath Data Model) chosen
    XDM (XQuery and XPath Data Model) is the formal, abstract data model that defines the types and structures of data processed by XQuery and XPath expressions.
  • B. XDS
    XDS (Cross-Enterprise Document Sharing) is an IHE IT Infrastructure profile that defines standards-based methods for registering, storing, and sharing clinical documents across healthcare enterprises.
  • C. X3
    X3 is the former designation of the standards body now known as INCITS, which oversees information technology standards in the United States.
  • D. XFree86
    XFree86 is an open-source implementation of the X Window System for Unix-like operating systems, historically used to provide graphical user interfaces on many Linux and BSD distributions.
  • E. XNM
    XNM is the IATA airport-style code assigned to Norwich railway station in Norwich, England, for use in integrated transport and ticketing systems.
  • 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.