Triple
T22330494
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | WebTest |
E552009
|
entity |
| Predicate | compatibleWith |
P203
|
FINISHED |
| Object | pytest |
—
|
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: pytest | Statement: [WebTest, compatibleWith, pytest]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: pytest Context triple: [WebTest, compatibleWith, pytest]
-
A.
pytest
chosen
pytest is a popular Python testing framework that simplifies writing, organizing, and running tests with a concise, expressive syntax and powerful plugin system.
-
B.
ctest
ctest is CMake’s built-in testing tool used to execute and manage automated tests for software projects.
-
C.
unittest
unittest is Python’s built-in unit testing framework that provides tools for organizing tests, checking results, and automating test execution.
-
D.
Pym Test Kitchen
Pym Test Kitchen is a Marvel-themed restaurant at Disney’s Avengers Campus that playfully uses “Pym Particle” technology as its concept to serve whimsically oversized and miniaturized foods.
-
E.
Testify
"Testify" is a blues-rock song by Stevie Ray Vaughan and Double Trouble, featured on their debut album "Texas Flood."
- 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_69e11e482f788190b78d1588fc26d606 |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f1577a9c348190b8662142afa832be |
completed | April 29, 2026, 12:57 a.m. |
Created at: April 16, 2026, 8:43 p.m.