extract_covid_entity | Codebase accompanying the paper Leveraging Event Specific
kandi X-RAY | extract_covid_entity Summary
kandi X-RAY | extract_covid_entity Summary
extract_covid_entity is a Python library. extract_covid_entity has no bugs, it has no vulnerabilities, it has a Permissive License and it has low support. However extract_covid_entity build file is not available. You can download it from GitHub.
Codebase accompanying the paper "Leveraging Event Specific and Chunk Span features to Extract COVID Events from tweets" - WNUT @ EMNLP 2020
Codebase accompanying the paper "Leveraging Event Specific and Chunk Span features to Extract COVID Events from tweets" - WNUT @ EMNLP 2020
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Support
extract_covid_entity has a low active ecosystem.
It has 5 star(s) with 1 fork(s). There are 1 watchers for this library.
It had no major release in the last 12 months.
extract_covid_entity has no issues reported. There are no pull requests.
It has a neutral sentiment in the developer community.
The latest version of extract_covid_entity is v0.0.1
Quality
extract_covid_entity has no bugs reported.
Security
extract_covid_entity has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.
License
extract_covid_entity is licensed under the MIT License. This license is Permissive.
Permissive licenses have the least restrictions, and you can use them in most projects.
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extract_covid_entity releases are available to install and integrate.
extract_covid_entity has no build file. You will be need to create the build yourself to build the component from source.
Installation instructions are not available. Examples and code snippets are available.
Top functions reviewed by kandi - BETA
kandi has reviewed extract_covid_entity and discovered the below as its top functions. This is intended to give you an instant insight into extract_covid_entity implemented functionality, and help decide if they suit your requirements.
- Create instances for each task
- Get the label from a tagged label
- Get the label for the given key
- Return a mapping of tokens to tweet tokens
- Get prediction scores
- Compute F1 score
- Normalize an answer
- Compute Gimme stats
- Translate label to appropriate label
- Extract subtask instances from a list of Tasks
- Splits the multitask_instances in train mode
- Write JSON to a file
- Log statistics for multitask data
- Read data from a jsonl file
- Read json file
- Format an elapsed time
- Adds marker for loss markers to the data
- Pick the label text for each task
- Determine the tweet id for the given prediction scores
- Make predictions for the given model
- Return the label for a label
- Save predictions as JSON
- Calculate TP FP FP FP FN
- Make predictions on the given dataset
- Get tweets from twitter API
- Calculate TP FP FP FN
Get all kandi verified functions for this library.
extract_covid_entity Key Features
No Key Features are available at this moment for extract_covid_entity.
extract_covid_entity Examples and Code Snippets
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Author = {Ayush Kaushal and Tejas Vaidhya},
Title = {Leveraging Event Specific and Chunk Span features to Extract COVID Events from tweets},
Year = {2020},
Eprint = {arXiv:2012.10052},
Doi = {10.18653/v1/2020.wnut-1.79},
}
Community Discussions
No Community Discussions are available at this moment for extract_covid_entity.Refer to stack overflow page for discussions.
Community Discussions, Code Snippets contain sources that include Stack Exchange Network
Vulnerabilities
No vulnerabilities reported
Install extract_covid_entity
You can download it from GitHub.
You can use extract_covid_entity like any standard Python library. You will need to make sure that you have a development environment consisting of a Python distribution including header files, a compiler, pip, and git installed. Make sure that your pip, setuptools, and wheel are up to date. When using pip it is generally recommended to install packages in a virtual environment to avoid changes to the system.
You can use extract_covid_entity like any standard Python library. You will need to make sure that you have a development environment consisting of a Python distribution including header files, a compiler, pip, and git installed. Make sure that your pip, setuptools, and wheel are up to date. When using pip it is generally recommended to install packages in a virtual environment to avoid changes to the system.
Support
For any new features, suggestions and bugs create an issue on GitHub.
If you have any questions check and ask questions on community page Stack Overflow .
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