Learning Interpretations Using Sequence Classification

Menno Zaanen, Janneke Loo
Proceedings of the Eleventh International Conference on Grammatical Inference, PMLR 21:220-223, 2012.

Abstract

In this paper we present a system that assigns interpretations, in the form of shallow semantic frame descriptions, to natural language sentences. The system searches for relevant patterns, consisting of words from the sentences, to identify the correct semantic frame and associated slot values. For each of these choices, a separate classifier is trained. Each classifier learns the boundaries between different languages, which each correspond to a particular class. The different classifiers each have their own viewpoint on the data depending on which aspect needs to be identified.

Cite this Paper

BibTeX
@InProceedings{pmlr-v21-vanzaanen12a, title = {Learning Interpretations Using Sequence Classification}, author = {Zaanen, Menno and Loo, Janneke}, booktitle = {Proceedings of the Eleventh International Conference on Grammatical Inference}, pages = {220--223}, year = {2012}, editor = {Heinz, Jeffrey and Higuera, Colin and Oates, Tim}, volume = {21}, series = {Proceedings of Machine Learning Research}, address = {University of Maryland, College Park, MD, USA}, month = {05--08 Sep}, publisher = {PMLR}, pdf = {http://proceedings.mlr.press/v21/vanzaanen12a/vanzaanen12a.pdf}, url = {https://proceedings.mlr.press/v21/vanzaanen12a.html}, abstract = {In this paper we present a system that assigns interpretations, in the form of shallow semantic frame descriptions, to natural language sentences. The system searches for relevant patterns, consisting of words from the sentences, to identify the correct semantic frame and associated slot values. For each of these choices, a separate classifier is trained. Each classifier learns the boundaries between different languages, which each correspond to a particular class. The different classifiers each have their own viewpoint on the data depending on which aspect needs to be identified.} }
Endnote
%0 Conference Paper %T Learning Interpretations Using Sequence Classification %A Menno Zaanen %A Janneke Loo %B Proceedings of the Eleventh International Conference on Grammatical Inference %C Proceedings of Machine Learning Research %D 2012 %E Jeffrey Heinz %E Colin Higuera %E Tim Oates %F pmlr-v21-vanzaanen12a %I PMLR %P 220--223 %U https://proceedings.mlr.press/v21/vanzaanen12a.html %V 21 %X In this paper we present a system that assigns interpretations, in the form of shallow semantic frame descriptions, to natural language sentences. The system searches for relevant patterns, consisting of words from the sentences, to identify the correct semantic frame and associated slot values. For each of these choices, a separate classifier is trained. Each classifier learns the boundaries between different languages, which each correspond to a particular class. The different classifiers each have their own viewpoint on the data depending on which aspect needs to be identified.
RIS
TY - CPAPER TI - Learning Interpretations Using Sequence Classification AU - Menno Zaanen AU - Janneke Loo BT - Proceedings of the Eleventh International Conference on Grammatical Inference DA - 2012/08/16 ED - Jeffrey Heinz ED - Colin Higuera ED - Tim Oates ID - pmlr-v21-vanzaanen12a PB - PMLR DP - Proceedings of Machine Learning Research VL - 21 SP - 220 EP - 223 L1 - http://proceedings.mlr.press/v21/vanzaanen12a/vanzaanen12a.pdf UR - https://proceedings.mlr.press/v21/vanzaanen12a.html AB - In this paper we present a system that assigns interpretations, in the form of shallow semantic frame descriptions, to natural language sentences. The system searches for relevant patterns, consisting of words from the sentences, to identify the correct semantic frame and associated slot values. For each of these choices, a separate classifier is trained. Each classifier learns the boundaries between different languages, which each correspond to a particular class. The different classifiers each have their own viewpoint on the data depending on which aspect needs to be identified. ER -
APA
Zaanen, M. & Loo, J.. (2012). Learning Interpretations Using Sequence Classification. Proceedings of the Eleventh International Conference on Grammatical Inference, in Proceedings of Machine Learning Research 21:220-223 Available from https://proceedings.mlr.press/v21/vanzaanen12a.html.

Related Material