MACE-AL-TREE (doi:10.11588/data/THPEBR)

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Part 2: Study Description
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Document Description

Citation

Title:

MACE-AL-TREE

Identification Number:

doi:10.11588/data/THPEBR

Distributor:

heiDATA

Date of Distribution:

2020-03-26

Version:

1

Bibliographic Citation:

Rehbein, Ines; Ruppenhofer, Josef, 2020, "MACE-AL-TREE", https://doi.org/10.11588/data/THPEBR, heiDATA, V1

Study Description

Citation

Title:

MACE-AL-TREE

Subtitle:

A method for error detection in dependency parse trees

Identification Number:

doi:10.11588/data/THPEBR

Authoring Entity:

Rehbein, Ines (Leibniz Institute for the German Language)

Ruppenhofer, Josef (Leibniz Institute for the German Language)

Distributor:

heiDATA

Access Authority:

Rehbein, Ines

Date of Deposit:

2019-07-31

Holdings Information:

https://doi.org/10.11588/data/THPEBR

Study Scope

Keywords:

Arts and Humanities, Computer and Information Science, Tool, Annotation error, Error detection, Dependency parse tree, Parsing, Treebanks, Noisy data

Topic Classification:

Annotation noise, Error detection in automatic parse trees, Error detection in parser output

Abstract:

An method for detecting noise in automatically annotated dependency parse trees, combining MACE (Hovy et al. 2013) with Active Learning.

Kind of Data:

program source code

Methodology and Processing

Sources Statement

Data Access

Other Study Description Materials

Related Materials

<p><strong>MACE (Multi-Annotator Competence Estimation)</strong>: A generative modelfor Multi-Annotator Competence Estimation</p> <p><strong>Link to resource:</strong> <a href="https://github.com/dirkhovy/MACE">https://github.com/dirkhovy/MACE</a></p> <p><strong>Reference:</strong></p> Hovy, D., Berg-Kirkpatrick, T., Vaswani, A., and Eduard Hovy (2013). Learning whom to trust with MACE. In <em>Proceedings of the 2013 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies</em>, pp. 1120&ndash;1130, June 9&ndash;14, 2013, Atlanta, Georgia. <a href="https://www.aclweb.org/anthology/N13-1132.pdf">https://www.aclweb.org/anthology/N13-1132.pdf</a>

<p>&nbsp;</p> <p><strong>Chu-Liu-Edmonds dependency decoding: </strong>The Chu-Liu-Edmonds maximum spanning algorithm from the TurboParser (Martins et al. 2009) provided by Anders Johannsen.<strong><br /></strong></p> <p><strong>License:</strong> GNU General Public License v3.0</p> <p><strong>Link to resource:</strong> <a href="https://github.com/andersjo/dependency_decoding">https://github.com/andersjo/dependency_decoding</a></p> <p><strong>Reference:</strong></p> <p><span style="left: 201.251px; top: 1275.55px; font-size: 14.944px; font-family: sans-serif; transform: scaleX(0.944782);">Andr&eacute; F. T. Martins, Noah A. Smith, and Eric P. Xing (2009). Concise Integer Linear Programming Formulations for Dependency Parsing. In <em>Proceedings of the Joint Conference of the 47th Annual Meeting of the ACL and the 4th International Joint Conference on Natural Language Processing of the AFNLP. </em>pp. 342&ndash;350,&nbsp;August 2-7, 2009, Suntec, Singapore, <br /></span></p>

Related Studies

In MACE-AL-TREE, we extend the model from MACE-AL (https://doi.org/10.11588/data/C2OQN4) to hierarchically structured data.

Related Publications

Citation

Title:

<p>Rehbein, I. and Ruppenhofer, J. (2018). Sprucing up the trees &ndash; error detection in treebanks. In <em>Proceedings of the 27th International Conference on Computational Linguistics</em>, pages 107&ndash;118, August 20-26, 2018, Santa Fe, New Mexico, USA. Association for Computational Linguistics.</p>

Bibliographic Citation:

<p>Rehbein, I. and Ruppenhofer, J. (2018). Sprucing up the trees &ndash; error detection in treebanks. In <em>Proceedings of the 27th International Conference on Computational Linguistics</em>, pages 107&ndash;118, August 20-26, 2018, Santa Fe, New Mexico, USA. Association for Computational Linguistics.</p>

Other Study-Related Materials

Label:

MACE-AL-TREE.zip

Notes:

application/zip