Triple

T14343826
Position Surface form Disambiguated ID Type / Status
Subject Java servlets E355663 entity
Predicate usedWith P4791 FINISHED
Object JavaServer Faces E200574 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: JavaServer Faces | Statement: [Java servlets, usedWith, JavaServer Faces]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: JavaServer Faces
Context triple: [Java servlets, usedWith, JavaServer Faces]
  • A. Jakarta Server Faces chosen
    Jakarta Server Faces is a component-based web framework for building server-side user interfaces in Java enterprise applications.
  • B. MyFaces
    MyFaces is an open-source implementation of the Jakarta Server Faces (JSF) framework that provides components and tools for building Java-based web user interfaces.
  • C. Facelets
    Facelets is a powerful view declaration language for building component-based user interfaces in Java web applications, particularly with Jakarta Server Faces.
  • D. Java EE
    Java EE is a widely used enterprise-grade Java platform specification for building scalable, distributed, and transactional server-side applications.
  • E. Jakarta Server Pages
    Jakarta Server Pages is a Jakarta EE web technology that enables developers to create dynamic, server-side HTML content using Java-based templates.
  • 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_69d82790a7e08190877e2d349b2e8d8e completed April 9, 2026, 10:26 p.m.
NER Named-entity recognition batch_69de8e89ed9c8190acdb647ee618e919 completed April 14, 2026, 6:59 p.m.
NED1 Entity disambiguation (via context triple) batch_69fd469d899081909103563f209dd944 completed May 8, 2026, 2:12 a.m.
Created at: April 10, 2026, 1:14 a.m.