document-level

#自然语言处理#[EMNLP 2022] An Open Toolkit for Knowledge Graph Extraction and Construction

[IJCAI 2021] Document-level Relation Extraction as Semantic Segmentation

#自然语言处理#Source code for ACL-IJCNLP 2021 Long paper: Document-level Event Extraction via Heterogeneous Graph-based Interaction Model with a Tracker.

PyTorch code for JEREX: Joint Entity-Level Relation Extractor

#自然语言处理#Code for paper Document-Level Paraphrase Generation with Sentence Rewriting and Reordering by Zhe Lin, Yitao Cai and Xiaojun Wan. This paper is accepted by Findings of EMNLP'21.

Code for our paper "Leveraging Document-Level Label Consistency for Named Entity Recognition" and "Uncertainty-Aware Sequence Labeling"

Cross Sentence Neural Machine Translation

Source code for paper "PRiSM: Enhancing Low-Resource Document-Level Relation Extraction with Relation-Aware Score Calibration", Findings of IJCNLP-AACL 2023

[AAAI 2021] PyTorch implementation for "A Graph-based Relevance Matching Model for Ad-hoc Retrieval"

Performing aspect-level sentiment classification using document-level knowledge based on the "Exploiting document knowledge for aspect-level sentiment classification" paper.

This is to dcument the steps needed to create a VSTO document Template (in C# using Visual Studio 2019)