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Hands-on tutorial on deep learning with a special focus on Natural Language Processing (NLP)
Code and data for ACL2016 article "Which argument is more convincing? Analyzing and predicting convincingness of Web arguments using bidirectional LSTM" by Ivan Habernal and Iryna Gurevych"
Supplementary data for the Unshared Task at the 3rd Argument Mining workshop, ACL 2016
BiLSTM-CNN-CRF architecture for sequence tagging using ELMo representations.
PropsDE is a tool to transform German sentences into proposition structures and to extract Open IE tuples from them.
A general framework for Interactive Multi-Document Summarization
Context-Aware Representations for Knowledge Base Relation Extraction
Accompanying code for our EMNLP 2018 Demo paper "Interactive Instance-based Evaluation of Knowledge Base Question Answering"
Accompanying code for our paper "Frame- and Entity-Based Knowledge for Common-Sense Argumentative Reasoning" at the 5th Workshop on Argument Mining @ EMNLP 2018.
Source code repository for our EMNLP paper on cross-domain claim identification
Annotations and code for the EMNLP 2018 paper 'Weeding out Conventionalized Metaphors: A Corpus of Novel Metaphor Annotations'
Experimental code for the paper 'Finding Convincing Arguments Using Scalable Bayesian Preference Learning'
Code for the paper "Multi-Task Learning for Argumentation Mining in Low-Resource Settings"
BiLSTM-CNN-CRF architecture for sequence tagging
Concatenated Power Mean Embeddings as Universal Cross-Lingual Sentence Representations
Files for Event Nugget Detection systems submitted to TAC 2015 shared task on Event Nugget Detection
Accompanying code for our COLING 2018 paper "Modeling Semantics with Gated Graph Neural Networks for Knowledge Base Question Answering"
Accompanying code for our LaTeCH-CLfL 2018 paper "One Size Fits All? A Simple LSTM for Non-literal Token- and Construction Level Classification"
An adaptation of MarMot morphological tagger for generic sequence-to-sequence tasks
Accompanying code for our ACL-2017 publication on Neural End-to-End Learning for Computational Argumentation Mining
Sentence Embeddings used in the GermEval-2017 Submission