Amazon Multilingual Counterfactual Dataset (AMCD)

Overview

Amazon Multilingual Counterfactual Dataset (AMCD)

This repository contains a dataset described in the paper:

I Wish I Would Have Loved This One, But I Didn’t – A Multilingual Dataset for Counterfactual Detection in Product Reviews. James O’Neill, Polina Rozenshtein, Ryuichi Kiryo, Motoko Kubota, Danushka Bollegala. EMNLP'21. arxiv version

The dataset contains sentences from Amazon customer reviews (sampled from Amazon product review dataset) annotated for counterfactual detection (CFD) binary classification. Counterfactual statements describe events that did not or cannot take place. Counterfactual statements may be identified as statements of the form – If p was true, then q would be true (i.e. assertions whose antecedent (p) and consequent (q) are known or assumed to be false).

The key features of this dataset are:

  • The dataset is multilingual and contains sentences in English, German, and Japanese.
  • The labeling was done by professional linguists and high quality was ensured.
  • The dataset is supplemented with the annotation guidelines and definitions, which were worked out by professional linguists. We also provide the clue word lists, which are typical for counterfactual sentences and were used for initial data filtering. The clue word lists were also compiled by professional linguists.

Please see paper for the data statistics, detailed description of data collection and annotation.

For the dataset format please see README.txt.

Cite

If you use this dataset in your research, please cite the paper.

License Summary

The documentation is made available under the Creative Commons Attribution-ShareAlike 4.0 International License. See the LICENSE file.

PyTorch implementation of convolutional neural networks-based text-to-speech synthesis models

Deepvoice3_pytorch PyTorch implementation of convolutional networks-based text-to-speech synthesis models: arXiv:1710.07654: Deep Voice 3: Scaling Tex

Ryuichi Yamamoto 1.8k Dec 30, 2022
Dope Wars game engine on StarkNet L2 roll-up

RYO Dope Wars game engine on StarkNet L2 roll-up. What TI-83 drug wars built as smart contract system. Background mechanism design notion here. Initia

104 Dec 04, 2022
Code for "Finetuning Pretrained Transformers into Variational Autoencoders"

transformers-into-vaes Code for Finetuning Pretrained Transformers into Variational Autoencoders (our submission to NLP Insights Workshop 2021). Gathe

Seongmin Park 22 Nov 26, 2022
code for modular summarization work published in ACL2021 by Krishna et al

This repository contains the code for running modular summarization pipelines as described in the publication Krishna K, Khosla K, Bigham J, Lipton ZC

Approximately Correct Machine Intelligence (ACMI) Lab 21 Nov 24, 2022
Espresso: A Fast End-to-End Neural Speech Recognition Toolkit

Espresso Espresso is an open-source, modular, extensible end-to-end neural automatic speech recognition (ASR) toolkit based on the deep learning libra

Yiming Wang 919 Jan 03, 2023
This repo contains simple to use, pretrained/training-less models for speaker diarization.

PyDiar This repo contains simple to use, pretrained/training-less models for speaker diarization. Supported Models Binary Key Speaker Modeling Based o

12 Jan 20, 2022
An example project using OpenPrompt under pytorch-lightning for prompt-based SST2 sentiment analysis model

pl_prompt_sst An example project using OpenPrompt under the framework of pytorch-lightning for a training prompt-based text classification model on SS

Zhiling Zhang 5 Oct 21, 2022
Paddle2.x version AI-Writer

Paddle2.x 版本AI-Writer 用魔改 GPT 生成网文。Tuned GPT for novel generation.

yujun 74 Jan 04, 2023
ConvBERT-Prod

ConvBERT 目录 0. 仓库结构 1. 简介 2. 数据集和复现精度 3. 准备数据与环境 3.1 准备环境 3.2 准备数据 3.3 准备模型 4. 开始使用 4.1 模型训练 4.2 模型评估 4.3 模型预测 5. 模型推理部署 5.1 基于Inference的推理 5.2 基于Serv

yujun 7 Apr 08, 2022
Japanese NLP Library

Japanese NLP Library Back to Home Contents 1 Requirements 1.1 Links 1.2 Install 1.3 History 2 Libraries and Modules 2.1 Tokenize jTokenize.py 2.2 Cabo

Pulkit Kathuria 144 Dec 27, 2022
Rhasspy 673 Dec 28, 2022
Hostapd-mac-tod-acl - Setup a hostapd AP with MAC ToD ACL

A brief explanation This script provides a quick way to setup a Time-of-day (Tod

2 Feb 03, 2022
Coreference resolution for English, German and Polish, optimised for limited training data and easily extensible for further languages

Coreferee Author: Richard Paul Hudson, msg systems ag 1. Introduction 1.1 The basic idea 1.2 Getting started 1.2.1 English 1.2.2 German 1.2.3 Polish 1

msg systems ag 169 Dec 21, 2022
Mkdocs + material + cool stuff

Modern-Python-Doc-Example mkdocs + material + cool stuff Doc is live here Features out of the box amazing good looking website thanks to mkdocs.org an

Francesco Saverio Zuppichini 61 Oct 26, 2022
Simple bots or Simbots is a library designed to create simple bots using the power of python. This library utilises Intent, Entity, Relation and Context model to create bots .

Simple bots or Simbots is a library designed to create simple chat bots using the power of python. This library utilises Intent, Entity, Relation and

14 Dec 15, 2021
Source code of the "Graph-Bert: Only Attention is Needed for Learning Graph Representations" paper

Graph-Bert Source code of "Graph-Bert: Only Attention is Needed for Learning Graph Representations". Please check the script.py as the entry point. We

14 Mar 25, 2022
Torchrecipes provides a set of reproduci-able, re-usable, ready-to-run RECIPES for training different types of models, across multiple domains, on PyTorch Lightning.

Recipes are a standard, well supported set of blueprints for machine learning engineers to rapidly train models using the latest research techniques without significant engineering overhead.Specifica

Meta Research 193 Dec 28, 2022
REST API for sentence tokenization and embedding using Multilingual Universal Sentence Encoder.

What is MUSE? MUSE stands for Multilingual Universal Sentence Encoder - multilingual extension (16 languages) of Universal Sentence Encoder (USE). MUS

Dani El-Ayyass 47 Sep 05, 2022
IndoBERTweet is the first large-scale pretrained model for Indonesian Twitter. Published at EMNLP 2021 (main conference)

IndoBERTweet 🐦 🇮🇩 1. Paper Fajri Koto, Jey Han Lau, and Timothy Baldwin. IndoBERTweet: A Pretrained Language Model for Indonesian Twitter with Effe

IndoLEM 40 Nov 30, 2022
A multi-voice TTS system trained with an emphasis on quality

TorToiSe Tortoise is a text-to-speech program built with the following priorities: Strong multi-voice capabilities. Highly realistic prosody and inton

James Betker 2.1k Jan 01, 2023