Triple
T18531196
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | PHPUnit Bridge |
E452833
|
entity |
| Predicate | supports |
P516
|
FINISHED |
| Object | PHPUnit |
—
|
NE NERFINISHED |
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: PHPUnit | Statement: [PHPUnit Bridge, supports, PHPUnit]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: PHPUnit Context triple: [PHPUnit Bridge, supports, PHPUnit]
-
A.
PHPUnit
chosen
PHPUnit is a widely used unit testing framework for PHP that provides tools for writing, organizing, and running automated tests.
-
B.
NUnit
NUnit is a popular open-source unit testing framework for .NET languages, widely used to write and run automated tests in C#.
-
C.
JUnit
JUnit is a widely used open-source unit testing framework for the Java programming language that supports test-driven development and automated testing.
-
D.
MUnit
MUnit is a testing framework designed for Mule applications that enables developers to create, automate, and run unit and integration tests within the MuleSoft ecosystem.
-
E.
Test::Unit
Test::Unit is a unit testing framework for the Ruby programming language that provides a structured way to write and run automated tests.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69d8d387b5548190aa030dad2cb4947e |
completed | April 10, 2026, 10:40 a.m. |
| NER | Named-entity recognition | batch_69e533fd0e348190ab3d4548f74b9b79 |
completed | April 19, 2026, 7:58 p.m. |
Created at: April 10, 2026, 11:37 a.m.