INSPIRED: A Transparent Dialogue Dataset for Interactive Semantic Parsing

Related tags

Deep LearningINSPIRED
Overview

INSPIRED: A Transparent Dialogue Dataset for Interactive Semantic Parsing

Existing studies on semantic parsing focus primarily on mapping a natural-language utterance to a corresponding logical form in one turn. However, because natural language can contain a great deal of ambiguity and variability, this is a difficult challenge. In this work, we investigate an interactive semantic parsing framework that explains the predicted logical form step by step in natural language and enables the user to make corrections through natural-language feedback for individual steps. We focus on question answering over knowledge bases (KBQA) as an instantiation of our framework, aiming to increase the transparency of the parsing process and help the user appropriately trust the final answer. To do so, we construct INSPIRED, a crowdsourced dialogue dataset derived from the ComplexWebQuestions dataset.

This repository will contain the dataset and code for our paper Towards Transparent Interactive Semantic Parsing via Step-by-Step Correction.

Data

Dataset Download

The dataset can be downloaded under this path: ./data/dataset.jsonl

Data Structure

In the dataset file, each line is a dictionary with several keys:

{
    "id": "ID number",
    "cwq_question": "Original complex question in CWQ dataset",
    "rephrased_question": "Rephrased complex question by workers",
    "rephrased_question_label": " 'Replacement' or 'Alternative' ",
    "question": "If rephrased_question_label is marked as 'Replacement', set the value the same as rephrased_question; Otherwise, set it the same as cwq_question",
    "final_answer": "Final answer for the complex question",
    "gold_parse": "Gold sparql query for complex question",
    "preprocessed_gold_parse": "Preprocessed gold parse with entities and prefix replaced",
    "predicted_parse": "Predicted sparql query by initial semantic parser",
    "gold_sub_lfs": "A list of gold sub-logical forms after decomposition",
    "pred_sub_lfs": "A list of predicted sub-logical forms after decomposition",
    "gold_sub_qs": [
        {
          "sub_id": "ID of sub questions",
          "sub_question": "Rephrased sub question",
          "temp_sub_question": "Templated sub question for gold sub-logical form",
          "answer": "Answer for each sub question",
        }, "..."], 
    "pred_sub_qs": [
        {
          "sub_id": "ID of sub questions",
          "sub_question": "Rephrased sub question",
          "temp_sub_question": "Templated sub question for predicted sub-logical form",
          "answer": "Answer for each sub question",
        }, "..."], 
    "feedback": "A list of human feedback"
    
}
MolRep: A Deep Representation Learning Library for Molecular Property Prediction

MolRep: A Deep Representation Learning Library for Molecular Property Prediction Summary MolRep is a Python package for fairly measuring algorithmic p

AI-Health @NSCC-gz 83 Dec 24, 2022
Toolbox of models, callbacks, and datasets for AI/ML researchers.

Pretrained SOTA Deep Learning models, callbacks and more for research and production with PyTorch Lightning and PyTorch Website • Installation • Main

Pytorch Lightning 1.4k Dec 30, 2022
A Large-Scale Dataset for Spinal Vertebrae Segmentation in Computed Tomography

A Large-Scale Dataset for Spinal Vertebrae Segmentation in Computed Tomography

ICT.MIRACLE lab 75 Dec 26, 2022
Covid19-Forecasting - An interactive website that tracks, models and predicts COVID-19 Cases

Covid-Tracker This is an interactive website that tracks, models and predicts CO

Adam Lahmadi 1 Feb 01, 2022
NPBG++: Accelerating Neural Point-Based Graphics

[CVPR 2022] NPBG++: Accelerating Neural Point-Based Graphics Project Page | Paper This repository contains the official Python implementation of the p

Ruslan Rakhimov 57 Dec 03, 2022
Pytorch implementation of VAEs for heterogeneous likelihoods.

Heterogeneous VAEs Beware: This repository is under construction 🛠️ Pytorch implementation of different VAE models to model heterogeneous data. Here,

Adrián Javaloy 35 Nov 29, 2022
Official implementation of "StyleCariGAN: Caricature Generation via StyleGAN Feature Map Modulation" (SIGGRAPH 2021)

StyleCariGAN: Caricature Generation via StyleGAN Feature Map Modulation This repository contains the official PyTorch implementation of the following

Wonjong Jang 270 Dec 30, 2022
This is the official pytorch implementation of AutoDebias, an automatic debiasing method for recommendation.

AutoDebias This is the official pytorch implementation of AutoDebias, a debiasing method for recommendation system. AutoDebias is proposed in the pape

Dong Hande 77 Nov 25, 2022
This is the official pytorch implementation of the BoxEL for the description logic EL++

BoxEL: Box EL++ Embedding This is the official pytorch implementation of the BoxEL for the description logic EL++. BoxEL++ is a geometric approach bas

1 Nov 03, 2022
Yas CRNN model training - Yet Another Genshin Impact Scanner

Yas-Train Yet Another Genshin Impact Scanner 又一个原神圣遗物导出器 介绍 该仓库为 Yas 的模型训练程序 相关资料 MobileNetV3 CRNN 使用 假设你会设置基本的pytorch环境。 生成数据集 python main.py gen 训练

wormtql 18 Jan 08, 2023
Model Serving Made Easy

The easiest way to build Machine Learning APIs BentoML makes moving trained ML models to production easy: Package models trained with any ML framework

BentoML 4.4k Jan 08, 2023
This repository contains the entire code for our work "Two-Timescale End-to-End Learning for Channel Acquisition and Hybrid Precoding"

Two-Timescale-DNN Two-Timescale End-to-End Learning for Channel Acquisition and Hybrid Precoding This repository contains the entire code for our work

QiyuHu 3 Mar 07, 2022
Cockpit is a visual and statistical debugger specifically designed for deep learning.

Cockpit: A Practical Debugging Tool for Training Deep Neural Networks

Felix Dangel 421 Dec 29, 2022
Source code for GNN-LSPE (Graph Neural Networks with Learnable Structural and Positional Representations)

Graph Neural Networks with Learnable Structural and Positional Representations Source code for the paper "Graph Neural Networks with Learnable Structu

Vijay Prakash Dwivedi 180 Dec 22, 2022
Differentiable Simulation of Soft Multi-body Systems

Differentiable Simulation of Soft Multi-body Systems Yi-Ling Qiao, Junbang Liang, Vladlen Koltun, Ming C. Lin [Paper] [Code] Updates The C++ backend s

YilingQiao 26 Dec 23, 2022
Code for ECCV 2020 paper "Contacts and Human Dynamics from Monocular Video".

Contact and Human Dynamics from Monocular Video This is the official implementation for the ECCV 2020 spotlight paper by Davis Rempe, Leonidas J. Guib

Davis Rempe 207 Jan 05, 2023
GAN Image Generator and Characterwise Image Recognizer with python

MODEL SUMMARY 모델의 구조는 크게 6단계로 나뉩니다. STEP 0: Input Image Predict 할 이미지를 모델에 입력합니다. STEP 1: Make Black and White Image STEP 1 은 입력받은 이미지의 글자를 흑색으로, 배경을

Juwan HAN 1 Feb 09, 2022
Independent and minimal implementations of some reinforcement learning algorithms using PyTorch (including PPO, A3C, A2C, ...).

PyTorch RL Minimal Implementations There are implementations of some reinforcement learning algorithms, whose characteristics are as follow: Less pack

Gemini Light 4 Dec 31, 2022
Implementation of Kaneko et al.'s MaskCycleGAN-VC model for non-parallel voice conversion.

MaskCycleGAN-VC Unofficial PyTorch implementation of Kaneko et al.'s MaskCycleGAN-VC (2021) for non-parallel voice conversion. MaskCycleGAN-VC is the

86 Dec 25, 2022
The codes for the work "Swin-Unet: Unet-like Pure Transformer for Medical Image Segmentation"

Swin-Unet The codes for the work "Swin-Unet: Unet-like Pure Transformer for Medical Image Segmentation"(https://arxiv.org/abs/2105.05537). A validatio

869 Jan 07, 2023