Triple

T5890976
Position Surface form Disambiguated ID Type / Status
Subject Darwinsys Java Cookbook examples E130986 entity
Predicate programmingLanguage P1592 FINISHED
Object Java E13745 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 | Statement: [Darwinsys Java Cookbook examples, programmingLanguage, Java]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Java
Context triple: [Darwinsys Java Cookbook examples, programmingLanguage, Java]
  • A. Java
    Java is a large, densely populated island in Indonesia that has long served as the country’s political and economic center.
  • B. Java chosen
    Java is a widely used, object-oriented programming language known for its platform independence and extensive use in enterprise, web, and mobile application development.
  • C. Java (Dzau)
    Java (Dzau) is a town in South Ossetia that serves as an important regional center and transport hub in the mountainous area north of Tskhinvali.
  • D. Javakade
    Javakade is a waterfront street on Amsterdam’s Java Island known for its modern residential architecture and harborside views.
  • E. Java Virtual Machine
    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.
  • 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_69c00857439c819095950754176aa58a completed March 22, 2026, 3:18 p.m.
NER Named-entity recognition batch_69c036b228508190b050acf51860a5c2 completed March 22, 2026, 6:36 p.m.
NED1 Entity disambiguation (via context triple) batch_69c0b114c53081908ea441b2a15c9ab9 completed March 23, 2026, 3:18 a.m.
Created at: March 22, 2026, 3:58 p.m.