DE eng

Search in the Catalogues and Directories

Hits 1 – 20 of 20

1
Universal Dependencies 2.9
Zeman, Daniel; Nivre, Joakim; Abrams, Mitchell. - : Universal Dependencies Consortium, 2021
BASE
Show details
2
Universal Dependencies 2.8.1
Zeman, Daniel; Nivre, Joakim; Abrams, Mitchell. - : Universal Dependencies Consortium, 2021
BASE
Show details
3
Universal Dependencies 2.8
Zeman, Daniel; Nivre, Joakim; Abrams, Mitchell. - : Universal Dependencies Consortium, 2021
BASE
Show details
4
Universal Dependencies 2.7
Zeman, Daniel; Nivre, Joakim; Abrams, Mitchell. - : Universal Dependencies Consortium, 2020
BASE
Show details
5
Universal Dependencies 2.6
Zeman, Daniel; Nivre, Joakim; Abrams, Mitchell. - : Universal Dependencies Consortium, 2020
BASE
Show details
6
Universal Dependencies 2.5
Zeman, Daniel; Nivre, Joakim; Abrams, Mitchell. - : Universal Dependencies Consortium, 2019
BASE
Show details
7
Universal Dependencies 2.4
Nivre, Joakim; Abrams, Mitchell; Agić, Željko. - : Universal Dependencies Consortium, 2019
BASE
Show details
8
Universal Dependencies 2.2
In: https://hal.archives-ouvertes.fr/hal-01930733 ; 2018 (2018)
BASE
Show details
9
Universal Dependencies 2.3
Nivre, Joakim; Abrams, Mitchell; Agić, Željko. - : Universal Dependencies Consortium, 2018
BASE
Show details
10
Universal Dependencies 2.2
Nivre, Joakim; Abrams, Mitchell; Agić, Željko. - : Universal Dependencies Consortium, 2018
BASE
Show details
11
Bleaching Text: Abstract Features for Cross-lingual Gender Prediction ...
Abstract: Gender prediction has typically focused on lexical and social network features, yielding good performance, but making systems highly language-, topic-, and platform-dependent. Cross-lingual embeddings circumvent some of these limitations, but capture gender-specific style less. We propose an alternative: bleaching text, i.e., transforming lexical strings into more abstract features. This study provides evidence that such features allow for better transfer across languages. Moreover, we present a first study on the ability of humans to perform cross-lingual gender prediction. We find that human predictive power proves similar to that of our bleached models, and both perform better than lexical models. ... : Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics ...
Keyword: Computation and Language cs.CL; FOS Computer and information sciences
URL: https://dx.doi.org/10.48550/arxiv.1805.03122
https://arxiv.org/abs/1805.03122
BASE
Hide details
12
Universal Dependencies 2.1
In: https://hal.inria.fr/hal-01682188 ; 2017 (2017)
BASE
Show details
13
Universal Dependencies 2.0 alpha (obsolete)
Nivre, Joakim; Agić, Željko; Ahrenberg, Lars. - : Universal Dependencies Consortium, 2017
BASE
Show details
14
Universal Dependencies 2.0
Nivre, Joakim; Agić, Željko; Ahrenberg, Lars. - : Universal Dependencies Consortium, 2017
BASE
Show details
15
Universal Dependencies 2.0 – CoNLL 2017 Shared Task Development and Test Data
Nivre, Joakim; Agić, Željko; Ahrenberg, Lars. - : Universal Dependencies Consortium, 2017
BASE
Show details
16
Universal Dependencies 2.1
Nivre, Joakim; Agić, Željko; Ahrenberg, Lars. - : Universal Dependencies Consortium, 2017
BASE
Show details
17
Universal Dependencies 1.4
Nivre, Joakim; Agić, Željko; Ahrenberg, Lars. - : Universal Dependencies Consortium, 2016
BASE
Show details
18
Universal Dependencies 1.3
Nivre, Joakim; Agić, Željko; Ahrenberg, Lars. - : Universal Dependencies Consortium, 2016
BASE
Show details
19
Universal Dependencies 1.1
Agić, Željko; Aranzabe, Maria Jesus; Atutxa, Aitziber. - : Universal Dependencies Consortium, 2015
BASE
Show details
20
Universal Dependencies 1.2
Nivre, Joakim; Agić, Željko; Aranzabe, Maria Jesus. - : Universal Dependencies Consortium, 2015
BASE
Show details

Catalogues
0
0
0
0
0
0
0
Bibliographies
0
0
0
0
0
0
0
0
0
Linked Open Data catalogues
0
Online resources
0
0
0
0
Open access documents
20
0
0
0
0
© 2013 - 2024 Lin|gu|is|tik | Imprint | Privacy Policy | Datenschutzeinstellungen ändern