Triple

T816105
Position Surface form Disambiguated ID Type / Status
Subject Jython E17654 entity
Predicate writtenIn P12727 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: [Jython, writtenIn, Java]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Java
Context triple: [Jython, writtenIn, 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 Platform, Standard Edition
    Java Platform, Standard Edition (Java SE) is the core Java computing platform that provides the fundamental libraries, virtual machine, and tools for developing and running general-purpose Java applications on desktops and servers.
  • D. AVA
    AVA is a designated American wine grape-growing region recognized for its unique geographic and climatic features that influence the character of wines produced there.
  • E. Java Platform, Micro Edition
    Java Platform, Micro Edition (Java ME) is a lightweight, modular version of the Java platform designed for resource-constrained devices such as mobile phones, embedded systems, and Internet of Things (IoT) devices.
  • 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_69a4937bcaac8190a322524ac6f45a5a completed March 1, 2026, 7:28 p.m.
NER Named-entity recognition batch_69a4ab5157b08190b6c8f2fd455f261e completed March 1, 2026, 9:10 p.m.
NED1 Entity disambiguation (via context triple) batch_69a76d8d1a448190be8494fa2776615a completed March 3, 2026, 11:23 p.m.
Created at: March 1, 2026, 7:38 p.m.