Triple
T10019936
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jakarta Bean Validation |
E200587
|
entity |
| Predicate | previousName |
P65
|
FINISHED |
| Object | Java Bean Validation |
E200587
|
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 Bean Validation | Statement: [Jakarta Bean Validation, previousName, Java Bean Validation]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Java Bean Validation Context triple: [Jakarta Bean Validation, previousName, Java Bean Validation]
-
A.
Jakarta Bean Validation
chosen
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.
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.
-
C.
Apache BVal
Apache BVal is an open-source implementation of the Jakarta Bean Validation specification provided by the Apache Software Foundation.
-
D.
JavaBeans
JavaBeans is a reusable software component model for the Java platform that defines conventions for building modular, configurable Java classes, often used in visual development environments.
-
E.
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.
- 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_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_69d28222773c81908eb84974fd6ce106 |
completed | April 5, 2026, 3:39 p.m. |
Created at: March 30, 2026, 8:53 p.m.