📖 A curated list of awesome resources dedicated to Relation Extraction, one of the most important tasks in Natural Language Processing (NLP).
-
Updated
Jan 27, 2022
📖 A curated list of awesome resources dedicated to Relation Extraction, one of the most important tasks in Natural Language Processing (NLP).
Statistics and accepted paper list of NLP conferences with arXiv link
Compendium of the resources available from top NLP conferences.
"Bootstrapping Relationship Extractors with Distributional Semantics" (Batista et al., 2015) in EMNLP'15 - Python implementation
Code for my EMNLP 2018 paper "SimpleQuestions Nearly Solved: A New Upperbound and Baseline Approach"
Code and data for paper "Dialog Intent Induction with Deep Multi-View Clustering", Hugh Perkins and Yi Yang, 2019, EMNLP 2019
Text classification with Sparse Composite Document Vectors.
Paper Lists, Notes and Slides, Focus on NLP. For summarization, please refer to https://github.com/xcfcode/Summarization-Papers
Implementation of EMNLP 2017 Paper "Natural Language Does Not Emerge 'Naturally' in Multi-Agent Dialog" using PyTorch and ParlAI
Code For TDEER: An Efficient Translating Decoding Schema for Joint Extraction of Entities and Relations (EMNLP 2021)
Code for EMNLP 2016 paper: Morphological Priors for Probabilistic Word Embeddings
Papers from top conferences and journals for event extraction in recent years
Official Code For TDEER: An Efficient Translating Decoding Schema for Joint Extraction of Entities and Relations (EMNLP 2021)
[EMNLP'21] Visual News: Benchmark and Challenges in News Image Captioning
Code for paper title "Learning Semantic Sentence Embeddings using Pair-wise Discriminator" COLING-2018
An unofficial code reproduction in the field of event extraction of EMNLP-19 paper "Event Detection with Multi-Order Graph Convolution and Aggregated Attention"
[EMNLP 2020] Collective HumAn OpinionS on Natural Language Inference Data
This library provides functionality for rapidly sharing and retrieving word embeddings over the internet. (EMNLP 2017).
Add a description, image, and links to the emnlp topic page so that developers can more easily learn about it.
To associate your repository with the emnlp topic, visit your repo's landing page and select "manage topics."