congressional_adversary | EMNLP 2020 paper “ Are ‘ Undocumented Workers ’ the Same

by awebson Python Version: Current License: MIT

X-Ray Key Features Code Snippets Community Discussions Vulnerabilities Install Support

kandi X-RAY | congressional_adversary Summary

congressional_adversary is a Python library typically used in Institutions, Learning, Education applications. congressional_adversary has no bugs, it has no vulnerabilities, it has build file available, it has a Permissive License and it has low support. You can download it from GitHub.

This repository accompanies our EMNLP 2020 paper “Are ‘Undocumented Workers’ the Same as ‘Illegal Aliens’? Disentangling Denotation and Connotation in Vector Spaces”. Paper. Recorded talk.

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Quality

Security

License

Reuse

Support

congressional_adversary has a low active ecosystem.

It has 8 star(s) with 1 fork(s). There are 4 watchers for this library.

It had no major release in the last 6 months.

There are 0 open issues and 1 have been closed. There are no pull requests.

It has a neutral sentiment in the developer community.

The latest version of congressional_adversary is current.

Quality

congressional_adversary has no bugs reported.

Security

congressional_adversary has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

License

congressional_adversary is licensed under the MIT License. This license is Permissive.

Permissive licenses have the least restrictions, and you can use them in most projects.

Reuse

congressional_adversary releases are not available. You will need to build from source code and install.

Build file is available. You can build the component from source.

Installation instructions, examples and code snippets are available.

Top functions reviewed by kandi - BETA

kandi has reviewed congressional_adversary and discovered the below as its top functions. This is intended to give you an instant insight into congressional_adversary implemented functionality, and help decide if they suit your requirements.

Partition a corpus into speakers
Extracts sentences from an underscored session
Tokenize sentences
Compute the accuracy for a given sequence of sequences
Predict the loss function
Parse XML files
Extract noun phrases from sentences
Sort a list of phrases
Compute the homogeneity of a query
Find the closest neighbors of the query
Return a summary of the homogeneity data
Calculate the homogeneity of the given query ids
Compute the homogeneity of the query
Aggregate the top k phrase
Perform a subsampling
Train the model
Save the model to the given path
Saves the given epoch
Converts tokens to underscore
Generate a vocabulary for the given corpus
Builds a vocabulary
Performs the forward computation
Builds the vocabulary
Extract named entities
Calculate the accuracy of a sentence
Converts a list of sentences into sentences
Splits a corpus into num_chunks

Get all kandi verified functions for this library.

congressional_adversary Key Features

No Key Features are available at this moment for congressional_adversary.

congressional_adversary Examples and Code Snippets

No Code Snippets are available at this moment for congressional_adversary.

Community Discussions

No Community Discussions are available at this moment for congressional_adversary.Refer to stack overflow page for discussions.

Community Discussions, Code Snippets contain sources that include Stack Exchange Network

Vulnerabilities

No vulnerabilities reported

Install congressional_adversary

(Python 3.7 or higher required.). Then, download the training and evaluation data from this Google Drive link, extract with your favorite tar command, and copy them to the data directory you just made. Note that this data is already fully preprocessed, so you don’t need to actually run any preprocessing script included in this repository. If you do, the raw corpus of Congressional Record is available from Gentzkow et al. (2019). The raw corpus of Partisan News is available from Kiesel et al. (2019).

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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