Triple

T307526
Position Surface form Disambiguated ID Type / Status
Subject IBM WebSphere E6335 entity
Predicate supportsLanguage P2177 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: [IBM WebSphere, supportsLanguage, Java]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Java
Context triple: [IBM WebSphere, supportsLanguage, 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. 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.
  • D. Java Sea
    The Java Sea is a shallow, tropical marginal sea in Indonesia, lying between the islands of Java and Borneo and known for its busy shipping routes and rich marine biodiversity.
  • E. Dart
    Dart is a client-optimized, object-oriented programming language developed by Google, primarily used for building web and cross-platform mobile applications (notably with the Flutter framework).
  • 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_69a2e79230508190b912ecb555aae17e completed Feb. 28, 2026, 1:03 p.m.
NER Named-entity recognition batch_69a2ea313be88190b4441f3ea41a99e2 completed Feb. 28, 2026, 1:14 p.m.
NED1 Entity disambiguation (via context triple) batch_69a3b4744d188190a38831b251ca4901 completed March 1, 2026, 3:37 a.m.
Created at: Feb. 28, 2026, 1:06 p.m.