Neural negation resolution for Norwegian
Negation is a pervasive phenomenon in natural language, that has important semantic effects and interacts with many other phenomena, such as factivity and sentiment/polarity. Consider the example sentence below:
It is by no means ideal
Here, the phrase by no means functions as a so-called negation cue and it has the sentiment-bearing word ideal within its so-called scope, and thereby serves to reverse the overall polarity from positive to negative.
The task of negation resolution in NLP aims at detecting negation cues and the scope of these cues in natural language. This requires annotated data, and while there are datasets for some high-resource languages, like English, Chinese and Spanish, there have until recently been no available resources for Norwegian.
The SANT (Sentiment Analysis for Norwegian Text) project is currently annotating a negation dataset for Norwegian, the first of its kind. The texts are taken from NoReC, a corpus of Norwegian reviews.
The focus of this thesis will be on the application of neural machine learning models to the task of negation resolution for Norwegian.