Accenture / Accenture/AmpliGraph
Implementation of PTransE
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- Dominant language
- Python
- Stars
- 2.2k
- Forks
- 257
- PR merge metrics
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Description
Background and Context
KGE algorithms in the literature span across multiple sub-classes such as models from different representation methods (e.g. DL-based, geometric based, etc). There is a sub-class of the literature that focuses on representing paths, starting with PTransE (2015).
Description
Since Ampligraph is becoming a default choice for KGE algorithm implementations, it would be helpful to include at least one algorithm from this class (e.g. PTransE). Could you please provide the implementation for PTransE?
Contributor guide
First steps
- Read the whole issue, then the project's contributing guide.
- Comment on the issue to say you are picking it up — it saves two people doing the same work.
- Fork the repository and make your change on a branch.
- Open a pull request that references the issue number.
Research direction
No file, test, or entry point is named. Start by reviewing the repository’s existing knowledge-graph embedding implementations and the PTransE literature to determine the required algorithm scope. Done means a complete PTransE implementation is integrated into AmpliGraph, with coverage for its expected behavior and validation against the project’s conventions.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- python
- Domain
- machine-learning
- Issue type
- Feature
- Difficulty
- 5/5
- Estimated time
- Over a week
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 25/100