Deep-Learning
By priya-dwivedi
OpenIE-standalone
By dair-iitd
Deep-Learning | OpenIE-standalone | |
---|---|---|
1 | 2 | |
3,336 | 559 | |
- | 1.8% | |
0.0 | 0.0 | |
about 1 year ago | over 2 years ago | |
Jupyter Notebook | PostScript | |
MIT License | GNU General Public License v3.0 or later |
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
Deep-Learning
Posts with mentions or reviews of Deep-Learning.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2021-05-14.
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Looking for a Claim Extraction/Sentence Segmentation Framework
Here is somebody else's code for finetuning T5, which should have very similar performance: https://github.com/priya-dwivedi/Deep-Learning/blob/master/wikihow-fine-tuning-T5/Tune_T5_WikiHow-Github.ipynb
OpenIE-standalone
Posts with mentions or reviews of OpenIE-standalone.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2021-05-21.
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KELM: Integrating Knowledge Graphs with Language Model Pre-Training Corpora
The field of Open Information Extraction has been trying to do that in a generic way for a long time, but the results are still far from good. A few references: OpenIE [1] Graphene [2] MinIE [3].
If you already have a Knowledge Graph (KG) and want to populate its instances from documents, that's called KG Population, and Knowledge-net [4] is a good reference.
Relation Extraction is another interesting approach if you know which kind of relations you're interested in, OpenNRE [5] a good example.
[1] https://github.com/dair-iitd/OpenIE-standalone
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Looking for a Claim Extraction/Sentence Segmentation Framework
if all you need is claim extraction I'd try with information extraction tools first such as openie https://github.com/dair-iitd/OpenIE-standalone
What are some alternatives?
When comparing Deep-Learning and OpenIE-standalone you can also consider the following projects:
OpenNRE - An Open-Source Package for Neural Relation Extraction (NRE)
minie - An open information extraction system that provides compact extractions
Graphene - Coreference Resolution, Simplification and Open Relation Extraction Pipeline
knowledge-net - KnowledgeNet: A Benchmark Dataset for Knowledge Base Population