Triple

T18255653
Position Surface form Disambiguated ID Type / Status
Subject Raku E437216 entity
Predicate runsOn P23 FINISHED
Object JVM NE NERFINISHED

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: JVM | Statement: [Raku, runsOn, JVM]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: JVM
Context triple: [Raku, runsOn, JVM]
  • A. Java Virtual Machine chosen
    The Java Virtual Machine (JVM) is a platform-independent runtime environment that executes compiled Java bytecode and enables languages like Java, Kotlin, and Groovy to run on diverse hardware and operating systems.
  • B. HotSpot JVM
    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.
  • C. K Virtual Machine
    K Virtual Machine is a lightweight Java virtual machine designed for resource-constrained devices such as mobile phones and embedded systems.
  • D. Java
    Java is a large, densely populated island in Indonesia that has long served as the country’s political and economic center.
  • E. 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.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69d8b913351c8190932b6a426de04b41 completed April 10, 2026, 8:47 a.m.
NER Named-entity recognition batch_69e4fd85ee548190a102611fcf709ad4 completed April 19, 2026, 4:06 p.m.
Created at: April 10, 2026, 10:34 a.m.