AREkit VS ARElight

Compare AREkit vs ARElight and see what are their differences.

AREkit

Document level Attitude and Relation Extraction toolkit (AREkit) for sampling and processing large text collections with ML and for ML (by nicolay-r)
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AREkit ARElight
3 3
52 35
- -
8.7 8.9
26 days ago 16 days ago
Python Python
MIT License MIT License
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.

AREkit

Posts with mentions or reviews of AREkit. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2022-06-18.

ARElight

Posts with mentions or reviews of ARElight. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2022-06-19.

What are some alternatives?

When comparing AREkit and ARElight you can also consider the following projects:

neural-networks-for-attitude-ex

zshot - Zero and Few shot named entity & relationships recognition

awesome-sentiment-attitude-extraction - A curated list of awesome sentiment analysis studies, in which attitude corresponds to the text position conveyed by Subject towards other Object mentioned in text such as: entities, events, etc.

DeepKE - [EMNLP 2022] An Open Toolkit for Knowledge Graph Extraction and Construction

FinBERT-QA - Financial Domain Question Answering with pre-trained BERT Language Model

ABSA-PyTorch - Aspect Based Sentiment Analysis, PyTorch Implementations. 基于方面的情感分析,使用PyTorch实现。

typeish - A runtime type checker for bash.... in bash. I'm not sorry.

PIXIU - This repository introduces PIXIU, an open-source resource featuring the first financial large language models (LLMs), instruction tuning data, and evaluation benchmarks to holistically assess financial LLMs. Our goal is to continually push forward the open-source development of financial artificial intelligence (AI).

BERT-Relation-Extraction - PyTorch implementation for "Matching the Blanks: Distributional Similarity for Relation Learning" paper

TextFooler - A Model for Natural Language Attack on Text Classification and Inference