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Related publications (35)

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An Annotated Corpus of Tonal Piano Music from the Long 19th Century

Martin Alois Rohrmeier, Fabian Claude Moss, Markus Franz Josef Neuwirth, Johannes Hentschel

We present a dataset of 264 annotated piano pieces of nine composers, composed in the long 19th century (https://doi.org/10.5281/zenodo.7483349). Annotations adhere to the DCML harmony annotation standard and include Roman numerals, phrase boundaries, and ...

Ohio State Univ, Sch Music2023

HIPE-2022 Shared Task Named Entity Datasets

Maud Ehrmann, Matteo Romanello

HIPE-2022 datasets used for the HIPE 2022 shared task on named entity recognition and classification (NERC) and entity linking (EL) in multilingual historical documents. HIPE-2022 datasets are based on six primary datasets assembled and prepared for the sh ...

2022

Natural Language Processing (NLP) has become increasingly utilized to provide adaptivity in educational applications. However, recent research has highlighted a variety of biases in pre-trained language models. While existing studies investigate bias in di ...

2022

We describe the DCU-EPFL submission to the IWPT 2021 Parsing Shared Task: From Raw Text to Enhanced Universal Dependencies. The task involves parsing Enhanced UD graphs, which are an extension of the basic dependency trees designed to be more facilitative ...

ASSOC COMPUTATIONAL LINGUISTICS-ACL2021

We propose the Recursive Non-autoregressive Graph-to-graph Transformer architecture (RNG-Tr) for the iterative refinement of arbitrary graphs through the recursive application of a non-autoregressive Graph-to-Graph Transformer and apply it to syntactic dep ...

2020

Impresso Named Entity Annotation Guidelines (CLEF-HIPE-2020)

Maud Ehrmann, Matteo Romanello

Impresso annotation guidelines used in the context of corpus annotation for the HIPE shared task (CLEF 2020 Evaluation Lab). CLEF-HIPE-2020 shared task: https://impresso.github.io/CLEF-HIPE-2020/ Impresso project: https://impresso-project.ch ...

2020

Graph-to-Graph Transformer for Transition-based Dependency Parsing

James Henderson, Alireza Mohammadshahi

We propose the Graph2Graph Transformer architecture for conditioning on and predicting arbitrary graphs, and apply it to the challenging task of transition-based dependency parsing. After proposing two novel Transformer models of transition-based dependenc ...

Association for Computational Linguistics2020

Partially-supervised Mention Detection

James Henderson

Learning to detect entity mentions without using syntactic information can be useful for integration and joint optimization with other tasks. However, it is common to have partially annotated data for this problem. Here, we investigate two approaches to de ...

ACL2020

FUNSD: A Dataset for Form Understanding in Noisy Scanned Documents

Jean-Philippe Thiran, Hazim Kemal Ekenel, Guillaume Jaume

We present a new dataset for form understanding in noisy scanned documents (FUNSD) that aims at extracting and structuring the textual content of forms. The dataset comprises 199 real, fully annotated, scanned forms. The documents are noisy and vary widely ...

IEEE2019

Implicit discourse relation classification with syntax-aware contextualized word representations

James Henderson

Automatically identifying implicit discourse relations requires an in-depth semantic understanding of the text fragments involved in such relations. While early work investigated the usefulness of different classes of input features, current state-of-the-a ...

2019