Convolution Neural Network for classification of semantic relations in a sentence
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Updated
Aug 24, 2017 - Python
Convolution Neural Network for classification of semantic relations in a sentence
Deep-learning model presented in "DataStories at SemEval-2017 Task 6: Siamese LSTM with Attention for Humorous Text Comparison".
SemEval-2017 Task 2 (subtask 1), supplemental material
word aligner for sentence similarity
Dependency graph stats and AMR paper
The code and data accompanying the ACL 2017 "outstanding award" publication "Vancouver Welcomes You! Minimalist Location Metonymy Resolution"
Sentiment Analysis with Deep Learning models. Implemented with Tensorflow and Keras.
Deep-learning model presented in "DataStories at SemEval-2017 Task 4: Deep LSTM with Attention for Message-level and Topic-based Sentiment Analysis".
Submissions for SemEval 2019 Task 8: Fact Checking in Community Question Answering Forums
基于Bert的文本情感分析模型(含semeval14数据集)
Taxonomy refinement method to improve domain-specific taxonomy systems.
The models developed by ASU_OPTO team as part of OffenseEval20 for Arabic tasks
cat🐈: the repo for the paper "Embarrassingly Simple Unsupervised Aspect extraction"
This repository contains the source code for the first and the second task of DeftEval 2020 competition, used by the University Politehnica of Bucharest (UPB) team to train and evaluate the models.
The Codebase for Quasi-Attention BERT Model for TABSA Tasks (AAAI '21)
Code of IIE-NLP-Eyas Team for ReCAM (Task 4) @SemEval2021 (https://arxiv.org/abs/2102.12777)
Semantic Textual Similarity (STS) measures the degree of equivalence in the underlying semantics of paired snippets of text.
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