Triple

T5767866
Position Surface form Disambiguated ID Type / Status
Subject JSONiq E127256 entity
Predicate hasAbbreviation P43 FINISHED
Object JSONiq E127256 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: JSONiq | Statement: [JSONiq, hasAbbreviation, JSONiq]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: JSONiq
Context triple: [JSONiq, hasAbbreviation, JSONiq]
  • A. JSONiq chosen
    JSONiq is a query and processing language designed specifically for JSON data, extending concepts from XQuery to work with hierarchical and semi-structured information.
  • B. XQuery
    XQuery is a functional query and programming language designed for extracting and manipulating data from XML documents and related data sources.
  • C. JSON
    JSON (JavaScript Object Notation) is a lightweight, text-based data interchange format widely used for transmitting structured data in web APIs and configuration files.
  • D. Jakarta JSON Processing
    Jakarta JSON Processing is a Jakarta EE specification that defines a standard API for parsing, generating, transforming, and querying JSON data in Java applications.
  • E. JQ
    JQ is the IATA airline designator used by Jetstar Airways, a major Australian low-cost carrier.
  • 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.