Triple

T7937050
Position Surface form Disambiguated ID Type / Status
Subject BPMN E184310 entity
Predicate relatedStandard P37 FINISHED
Object BPEL E545129 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: BPEL | Statement: [BPMN, relatedStandard, BPEL]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: BPEL
Context triple: [BPMN, relatedStandard, BPEL]
  • A. BPEL chosen
    BPEL (Business Process Execution Language) is an XML-based language used to define and orchestrate business processes and web services interactions in a standardized, executable form.
  • B. BPMN
    BPMN (Business Process Model and Notation) is a standardized graphical notation used to model and visualize business processes in a workflow.
  • C. BEA WebLogic Workshop
    BEA WebLogic Workshop is an integrated development environment designed by BEA Systems to simplify building Java-based enterprise and web services applications on the WebLogic platform.
  • D. ESB
    ESB is the IATA airport code for Esenboğa International Airport, the main airport serving Ankara, Turkey.
  • E. AquaLogic Enterprise Service Bus
    AquaLogic Enterprise Service Bus is a middleware platform that enables integration and orchestration of services and applications within a service-oriented architecture (SOA).
  • 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_69ca8290c21c8190906a5ca6fe2b03c4 completed March 30, 2026, 2:02 p.m.
NER Named-entity recognition batch_69cb3aef2394819086eea1f6ab117aed completed March 31, 2026, 3:09 a.m.
NED1 Entity disambiguation (via context triple) batch_69cb5c0a96ac819099ad30fb925eb329 completed March 31, 2026, 5:30 a.m.
Created at: March 30, 2026, 5:08 p.m.