Triple

T10019959
Position Surface form Disambiguated ID Type / Status
Subject Jakarta Bean Validation E200587 entity
Predicate hasImplementation P3697 FINISHED
Object Hibernate Validator
Hibernate Validator is the reference implementation of the Jakarta Bean Validation specification, providing a comprehensive framework for declarative validation of Java objects and their constraints.
E836365 NE FINISHED

How this triple was built (4 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: Hibernate Validator | Statement: [Jakarta Bean Validation, hasImplementation, Hibernate Validator]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Hibernate Validator
Context triple: [Jakarta Bean Validation, hasImplementation, Hibernate Validator]
  • A. Jakarta Bean Validation
    Jakarta Bean Validation is a Jakarta EE specification that defines a standard, annotation-based way to declare and enforce constraints on Java object models, typically used for validating user input and application data.
  • B. Validator
    Validator is a Symfony component that provides a flexible validation system for checking and enforcing constraints on data and objects in PHP applications.
  • C. ExampleValidator
    ExampleValidator is a TensorFlow Extended component that automatically analyzes input data to detect anomalies and validate examples before they are used in machine learning pipelines.
  • D. Colander validation library
    Colander validation library is a Python package for declaratively defining and validating data structures, often used for configuration and web form data.
  • E. Jhiben Hot Spring
    Jhiben Hot Spring is a popular hot spring resort area in southeastern Taiwan known for its natural thermal waters, scenic mountain surroundings, and spa facilities.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Hibernate Validator
Triple: [Jakarta Bean Validation, hasImplementation, Hibernate Validator]
Generated description
Hibernate Validator is the reference implementation of the Jakarta Bean Validation specification, providing a comprehensive framework for declarative validation of Java objects and their constraints.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Hibernate Validator
Target entity description: Hibernate Validator is the reference implementation of the Jakarta Bean Validation specification, providing a comprehensive framework for declarative validation of Java objects and their constraints.
  • A. Jakarta Bean Validation
    Jakarta Bean Validation is a Jakarta EE specification that defines a standard, annotation-based way to declare and enforce constraints on Java object models, typically used for validating user input and application data.
  • B. Validator
    Validator is a Symfony component that provides a flexible validation system for checking and enforcing constraints on data and objects in PHP applications.
  • C. ExampleValidator
    ExampleValidator is a TensorFlow Extended component that automatically analyzes input data to detect anomalies and validate examples before they are used in machine learning pipelines.
  • D. Colander validation library
    Colander validation library is a Python package for declaratively defining and validating data structures, often used for configuration and web form data.
  • E. Jhiben Hot Spring
    Jhiben Hot Spring is a popular hot spring resort area in southeastern Taiwan known for its natural thermal waters, scenic mountain surroundings, and spa facilities.
  • F. None of above. chosen

Provenance (5 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_69ca831c45f08190ac1505cc15076608 completed March 30, 2026, 2:05 p.m.
NER Named-entity recognition batch_69cdcd777b208190ad75eac79eec0c2f completed April 2, 2026, 1:59 a.m.
NED1 Entity disambiguation (via context triple) batch_69d26aaa38188190aed8c18eccd8a79d completed April 5, 2026, 1:59 p.m.
NEDg Description generation batch_69d26b84271881909c3a1b8a05e2c8a2 completed April 5, 2026, 2:02 p.m.
NED2 Entity disambiguation (via description) batch_69d26f50dc008190866f0ba45b671560 completed April 5, 2026, 2:18 p.m.
Created at: March 30, 2026, 8:53 p.m.