https://github.com/nicolay-r/ruattitudes
Dataset as a part of RANLP'2019 paper "Distant Supervision for Sentiment Attitude Extraction"
https://github.com/nicolay-r/ruattitudes
attitude-determination dataset distant-supervision relation-extraction
Last synced: 6 months ago
JSON representation
Dataset as a part of RANLP'2019 paper "Distant Supervision for Sentiment Attitude Extraction"
- Host: GitHub
- URL: https://github.com/nicolay-r/ruattitudes
- Owner: nicolay-r
- License: mit
- Created: 2019-07-20T09:22:31.000Z (about 6 years ago)
- Default Branch: master
- Last Pushed: 2023-10-01T21:59:14.000Z (about 2 years ago)
- Last Synced: 2025-02-12T00:39:04.263Z (8 months ago)
- Topics: attitude-determination, dataset, distant-supervision, relation-extraction
- Language: Python
- Homepage: https://www.aclweb.org/anthology/R19-1118/
- Size: 9.73 MB
- Stars: 1
- Watchers: 5
- Forks: 1
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
Awesome Lists containing this project
README
# RuAttitudes 2.0
[](https://github.com/nicolay-r/arekit-ss#usage)
> 📓 **Update 01 October 2023**: this collection **is now available in [arekit-ss](https://github.com/nicolay-r/arekit-ss)**
> for a [quick sampling](https://github.com/nicolay-r/arekit-ss#usage) of contexts with all subject-object relation mentions with just **single script into
> `JSONL/CSV/SqLite`** including (optional) language transfering 🔥 [[Learn more ...]](https://github.com/nicolay-r/arekit-ss#usage)
**RuAttitudes** -- is a collection of automatically labeled sentiment attitudes,
which is developed using **distant supervision** (DS) approach.
It is considered as an application for machine learning model training.
This repository provides a collection and **reader** (written in Python).
> News processing workflow, version 2.0 [[code]](https://github.com/nicolay-r/frame-based-attitude-extraction-workflow/tree/v2.0)
## Download
[RuAttitudes-2.0-Base (2.8 mln. news processed)](https://www.dropbox.com/s/y39vqzzjumqhce1/ruattitudes_20_base.zip?dl=1)
[RuAttitudes-2.0-Large (8.8 mln. news processed)](https://www.dropbox.com/s/43iqoxlyh38qk8u/ruattitudes_20_large.zip?dl=1)
# Contents
* [Format Description](#quick-start-format-description)
* [Reader](#collection-reader) 
* [References](#references)
## Format Descriptions
See the following [documentation](docs/Format.md).
## Collection Reader
[](https://github.com/nicolay-r/arekit-ss#usage)
> 📓 **Update 01 October 2023**: this collection **is now available in [arekit-ss](https://github.com/nicolay-r/arekit-ss)**
> for a [quick sampling](https://github.com/nicolay-r/arekit-ss#usage) of contexts with all subject-object relation mentions with just **single script into
> `JSONL/CSV/SqLite`** including (optional) language transfering 🔥 [[Learn more ...]](https://github.com/nicolay-r/arekit-ss#usage)
Folder `reader` contains a collection reader (source file parsers), written in Python-3.6.
Please refer to [read.py](read.py), as it provides an example of how this collection could be parsed/readed.
## References
```
@inproceedings{rusnachenko2021language,
title={Language Models Application in Sentiment Attitude Extraction Task},
author={Rusnachenko, Nicolay},
booktitle={Proceedings of the Institute for System Programming of the RAS (Proceedings of ISP RAS), vol.33},
year={2021},
number={3},
pages={199--222},
authorvak={true},
authorconf={false},
language={russian}
}
```