Triple

T575062
Position Surface form Disambiguated ID Type / Status
Subject Java E13745 entity
Predicate runsOn P23 FINISHED
Object Java Virtual Machine E68047 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: Java Virtual Machine | Statement: [Java, runsOn, Java Virtual Machine]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Java Virtual Machine
Context triple: [Java, runsOn, Java Virtual Machine]
  • A. HotSpot JVM chosen
    HotSpot JVM is a high-performance Java Virtual Machine known for its advanced just-in-time compilation and adaptive optimization techniques, originally developed by Sun Microsystems.
  • B. Java
    Java is a large, densely populated island in Indonesia that has long served as the country’s political and economic center.
  • C. Java
    Java is a widely used, object-oriented programming language known for its platform independence and extensive use in enterprise, web, and mobile application development.
  • D. Android Dalvik VM
    Android Dalvik VM is the original process-virtual-machine-based runtime used by early versions of the Android operating system to execute applications compiled to Dalvik bytecode.
  • E. VirtualBox
    VirtualBox is a popular open-source virtualization platform that allows users to run multiple operating systems simultaneously on a single physical machine.
  • 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_69a4933fa4d88190a7949cc83c08c5c1 completed March 1, 2026, 7:27 p.m.
NER Named-entity recognition batch_69a49b4c23548190a3b883239c7c78c8 completed March 1, 2026, 8:02 p.m.
NED1 Entity disambiguation (via context triple) batch_69a4ff4c3df48190a886a8d3c633d417 completed March 2, 2026, 3:09 a.m.
Created at: March 1, 2026, 7:33 p.m.