Add to ORKGWe use Google’s open source neural network framework, SyntaxNet, to train a fully automatic part-of-speech language tagger for Norwegian Bokmål and Nynorsk. Using SyntaxNet, we are able to get comparable results with other tagger when tagging Bokmål and Nynorsk with part-of-speech. Both taggers are available and released as open source
This project explores the expansion of an existing language recognition system for use with the Norw...
Neural networks are one of the most efficient techniques for learning from scarce data. This propert...
This article discusses the use of a monolingual dictionary (Bokmålsordboka) as basis for a wordnet f...
We use Google’s open source neural network framework, SyntaxNet, to train a fully automatic part-of-...
We use Google’s open source neural network framework, SyntaxNet, to train a fully automatic part-of-...
This paper describes an evaluation of five data-driven part-of-speech (PoS) taggers for spoken Norwe...
In this thesis we look at how we can develop automated analysis tools for Norwegian text. We look at...
Proceedings of the 16th Nordic Conference of Computational Linguistics NODALIDA-2007. Editors: Jo...
In some languages, Named Entity Recognition (NER) is severely hindered by complex linguistic structu...
In some languages, Named Entity Recognition (NER) is severely hindered by complex linguistic structu...
In this paper a Neural Network is designed for Part-of-Speech Tagging of Dutch text. Our approach us...
We describe the development of a two-way shallow-transfer machine translation system between Norwegi...
This paper investigates interactions in parser performance for the two official standards for writte...
This paper first shows how part-of-speech tags cen be ambiguous and why it is necessary to disambigu...
Text corpora which are tagged with part-of-speech information are useful in many areas of linguistic...
This project explores the expansion of an existing language recognition system for use with the Norw...
Neural networks are one of the most efficient techniques for learning from scarce data. This propert...
This article discusses the use of a monolingual dictionary (Bokmålsordboka) as basis for a wordnet f...
We use Google’s open source neural network framework, SyntaxNet, to train a fully automatic part-of-...
We use Google’s open source neural network framework, SyntaxNet, to train a fully automatic part-of-...
This paper describes an evaluation of five data-driven part-of-speech (PoS) taggers for spoken Norwe...
In this thesis we look at how we can develop automated analysis tools for Norwegian text. We look at...
Proceedings of the 16th Nordic Conference of Computational Linguistics NODALIDA-2007. Editors: Jo...
In some languages, Named Entity Recognition (NER) is severely hindered by complex linguistic structu...
In some languages, Named Entity Recognition (NER) is severely hindered by complex linguistic structu...
In this paper a Neural Network is designed for Part-of-Speech Tagging of Dutch text. Our approach us...
We describe the development of a two-way shallow-transfer machine translation system between Norwegi...
This paper investigates interactions in parser performance for the two official standards for writte...
This paper first shows how part-of-speech tags cen be ambiguous and why it is necessary to disambigu...
Text corpora which are tagged with part-of-speech information are useful in many areas of linguistic...
This project explores the expansion of an existing language recognition system for use with the Norw...
Neural networks are one of the most efficient techniques for learning from scarce data. This propert...
This article discusses the use of a monolingual dictionary (Bokmålsordboka) as basis for a wordnet f...