PyTorch implementation of the end-to-end coreference resolution model with different higher-order inference methods.

Overview

End-to-End Coreference Resolution with Different Higher-Order Inference Methods

This repository contains the implementation of the paper: Revealing the Myth of Higher-Order Inference in Coreference Resolution.

Architecture

The basic end-to-end coreference model is a PyTorch re-implementation based on the TensorFlow model following similar preprocessing (see this repository).

There are four higher-order inference (HOI) methods experimented: Attended Antecedent, Entity Equalization, Span Clustering, and Cluster Merging. All are included here except for Entity Equalization which is experimented in the equivalent TensorFlow environment (see this separate repository).

Files:

Basic Setup

Set up environment and data for training and evaluation:

  • Install Python3 dependencies: pip install -r requirements.txt
  • Create a directory for data that will contain all data files, models and log files; set data_dir = /path/to/data/dir in experiments.conf
  • Prepare dataset (requiring OntoNotes 5.0 corpus): ./setup_data.sh /path/to/ontonotes /path/to/data/dir

For SpanBERT, download the pretrained weights from this repository, and rename it /path/to/data/dir/spanbert_base or /path/to/data/dir/spanbert_large accordingly.

Evaluation

Provided trained models:

The name of each directory corresponds with a configuration in experiments.conf. Each directory has two trained models inside.

If you want to use the official evaluator, download and unzip conll 2012 scorer under this directory.

Evaluate a model on the dev/test set:

  • Download the corresponding model directory and unzip it under data_dir
  • python evaluate.py [config] [model_id] [gpu_id]
    • e.g. Attended Antecedent:python evaluate.py train_spanbert_large_ml0_d2 May08_12-38-29_58000 0

Prediction

Prediction on custom input: see python predict.py -h

  • Interactive user input: python predict.py --config_name=[config] --model_identifier=[model_id] --gpu_id=[gpu_id]
    • E.g. python predict.py --config_name=train_spanbert_large_ml0_d1 --model_identifier=May10_03-28-49_54000 --gpu_id=0
  • Input from file (jsonlines file of this format): python predict.py --config_name=[config] --model_identifier=[model_id] --gpu_id=[gpu_id] --jsonlines_path=[input_path] --output_path=[output_path]

Training

python run.py [config] [gpu_id]

  • [config] can be any configuration in experiments.conf
  • Log file will be saved at your_data_dir/[config]/log_XXX.txt
  • Models will be saved at your_data_dir/[config]/model_XXX.bin
  • Tensorboard is available at your_data_dir/tensorboard

Configurations

Some important configurations in experiments.conf:

  • data_dir: the full path to the directory containing dataset, models, log files
  • coref_depth and higher_order: controlling the higher-order inference module
  • bert_pretrained_name_or_path: the name/path of the pretrained BERT model (HuggingFace BERT models)
  • max_training_sentences: the maximum segments to use when document is too long; for BERT-Large and SpanBERT-Large, set to 3 for 32GB GPU or 2 for 24GB GPU

Citation

@inproceedings{xu-choi-2020-revealing,
    title = "Revealing the Myth of Higher-Order Inference in Coreference Resolution",
    author = "Xu, Liyan  and  Choi, Jinho D.",
    booktitle = "Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP)",
    month = nov,
    year = "2020",
    publisher = "Association for Computational Linguistics",
    url = "https://www.aclweb.org/anthology/2020.emnlp-main.686",
    pages = "8527--8533"
}
Owner
Liyan
PhD student at Emory University (NLP Lab).
Liyan
Lip Reading - Cross Audio-Visual Recognition using 3D Convolutional Neural Networks

Lip Reading - Cross Audio-Visual Recognition using 3D Convolutional Neural Networks - Official Project Page This repository contains the code develope

Amirsina Torfi 1.7k Dec 18, 2022
Pytorch Implementation of Value Retrieval with Arbitrary Queries for Form-like Documents.

Value Retrieval with Arbitrary Queries for Form-like Documents Introduction Pytorch Implementation of Value Retrieval with Arbitrary Queries for Form-

Salesforce 13 Sep 15, 2022
NDE: Climate Modeling with Neural Diffusion Equation, ICDM'21

Climate Modeling with Neural Diffusion Equation Introduction This is the repository of our accepted ICDM 2021 paper "Climate Modeling with Neural Diff

Jeehyun Hwang 5 Dec 18, 2022
The code repository for EMNLP 2021 paper "Vision Guided Generative Pre-trained Language Models for Multimodal Abstractive Summarization".

Vision Guided Generative Pre-trained Language Models for Multimodal Abstractive Summarization [Paper] accepted at the EMNLP 2021: Vision Guided Genera

CAiRE 42 Jan 07, 2023
Computer Vision is an elective course of MSAI, SCSE, NTU, Singapore

[AI6122] Computer Vision is an elective course of MSAI, SCSE, NTU, Singapore. The repository corresponds to the AI6122 of Semester 1, AY2021-2022, starting from 08/2021. The instructor of this course

HT. Li 5 Sep 12, 2022
Implementation of "StrengthNet: Deep Learning-based Emotion Strength Assessment for Emotional Speech Synthesis"

StrengthNet Implementation of "StrengthNet: Deep Learning-based Emotion Strength Assessment for Emotional Speech Synthesis" https://arxiv.org/abs/2110

RuiLiu 65 Dec 20, 2022
Official PyTorch implementation of paper: Standardized Max Logits: A Simple yet Effective Approach for Identifying Unexpected Road Obstacles in Urban-Scene Segmentation (ICCV 2021 Oral Presentation)

SML (ICCV 2021, Oral) : Official Pytorch Implementation This repository provides the official PyTorch implementation of the following paper: Standardi

SangHun 61 Dec 27, 2022
Colossal-AI: A Unified Deep Learning System for Large-Scale Parallel Training

ColossalAI An integrated large-scale model training system with efficient parallelization techniques. arXiv: Colossal-AI: A Unified Deep Learning Syst

HPC-AI Tech 7.9k Jan 08, 2023
DeiT: Data-efficient Image Transformers

DeiT: Data-efficient Image Transformers This repository contains PyTorch evaluation code, training code and pretrained models for DeiT (Data-Efficient

Facebook Research 3.2k Jan 06, 2023
An implementation of the AlphaZero algorithm for Gomoku (also called Gobang or Five in a Row)

AlphaZero-Gomoku This is an implementation of the AlphaZero algorithm for playing the simple board game Gomoku (also called Gobang or Five in a Row) f

Junxiao Song 2.8k Dec 26, 2022
All materials of Cassandra Event, Udyam'22

Cassandra 2022 Workspace Workshop Materials Workshop-1 Workshop-2 Workshop-3 Workshop-4 Assignments Assignment-1 Assignment-2 Assignment-3 Resources P

36 Dec 31, 2022
VID-Fusion: Robust Visual-Inertial-Dynamics Odometry for Accurate External Force Estimation

VID-Fusion VID-Fusion: Robust Visual-Inertial-Dynamics Odometry for Accurate External Force Estimation Authors: Ziming Ding , Tiankai Yang, Kunyi Zhan

ZJU FAST Lab 86 Nov 18, 2022
This repository contains all the code and materials distributed in the 2021 Q-Programming Summer of Qode.

Q-Programming Summer of Qode This repository contains all the code and materials distributed in the Q-Programming Summer of Qode. If you want to creat

Sammarth Kumar 11 Jun 11, 2021
Generic Event Boundary Detection: A Benchmark for Event Segmentation

Generic Event Boundary Detection: A Benchmark for Event Segmentation We release our data annotation & baseline codes for detecting generic event bound

47 Nov 22, 2022
Multi-task Self-supervised Object Detection via Recycling of Bounding Box Annotations (CVPR, 2019)

Multi-task Self-supervised Object Detection via Recycling of Bounding Box Annotations (CVPR 2019) To make better use of given limited labels, we propo

126 Sep 13, 2022
Detail-Preserving Transformer for Light Field Image Super-Resolution

DPT Official Pytorch implementation of the paper "Detail-Preserving Transformer for Light Field Image Super-Resolution" accepted by AAAI 2022 . Update

50 Jan 01, 2023
Doosan robotic arm, simulation, control, visualization in Gazebo and ROS2 for Reinforcement Learning.

Robotic Arm Simulation in ROS2 and Gazebo General Overview This repository includes: First, how to simulate a 6DoF Robotic Arm from scratch using GAZE

David Valencia 12 Jan 02, 2023
Meta Language-Specific Layers in Multilingual Language Models

Meta Language-Specific Layers in Multilingual Language Models This repo contains the source codes for our paper On Negative Interference in Multilingu

Zirui Wang 20 Feb 13, 2022
Joint detection and tracking model named DEFT, or ``Detection Embeddings for Tracking.

DEFT: Detection Embeddings for Tracking DEFT: Detection Embeddings for Tracking, Mohamed Chaabane, Peter Zhang, J. Ross Beveridge, Stephen O'Hara

Mohamed Chaabane 253 Dec 18, 2022
An implementation of quantum convolutional neural network with MindQuantum. Huawei, classifying MNIST dataset

关于实现的一点说明 山东大学 2020级 苏博南 www.subonan.com 文件说明 tools.py 这里面主要有两个函数: resize(a, lenb) 这其实是我找同学写的一个小算法hhh。给出一个$28\times 28$的方阵a,返回一个$lenb\times lenb$的方阵。因

ぼっけなす 2 Aug 29, 2022