Triple
T34594900
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | CPython Git repository |
E888282
|
entity |
| Predicate | instanceOf |
P0
|
FINISHED |
| Object | Python implementation repository |
C1443
|
CONCEPT FINISHED |
How this triple was built (1 step)
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.
CD
Concept disambiguation
gpt-5-mini-2025-08-07
Target class: Python implementation repository Context triple: [CPython Git repository, instanceOf, Python implementation repository]
-
A.
Python implementation
chosen
A Python implementation is a concrete realization of a program, algorithm, or system written in the Python programming language, following its syntax, semantics, and standard libraries to achieve specified functionality.
-
B.
Git repository
A Git repository is a version-controlled data structure that stores a project's files, their complete revision history, and metadata, enabling tracking, collaboration, and management of changes over time.
-
C.
Python SDK
A Python SDK is a collection of Python modules, tools, and documentation that simplifies integrating and interacting with a specific API, service, or platform within Python applications.
-
D.
Git repository hosting service
A Git repository hosting service is an online platform that stores, manages, and facilitates collaboration on Git-based source code repositories, providing features like version control, access control, issue tracking, and integration with development tools.
-
E.
machine learning model repository
A machine learning model repository is a centralized system for storing, versioning, organizing, and sharing trained models and their associated metadata throughout their lifecycle.
- F. None of above.
Provenance (1 batch)
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_69f349d3bfcc81909874c99e646fb3ea |
completed | April 30, 2026, 12:23 p.m. |
Created at: May 1, 2026, 2:03 a.m.