Coreference Resolution for Swedish

Sammanfattning

This report explores possible avenues for developing coreference resolution methods for Swedish. Coreference resolution is an important topic within natural language processing, as it is used as a preprocessing step in various information extraction tasks. The topic has been studied extensively for English, but much less so for smaller languages such as Swedish. In this report we adapt two coreference resolution algorithms that were originally used for English, for use on Swedish texts. One algorithm is entirely rule-based, while the other uses machine learning. We have also annotated a Swedish dataset to be used for training and evaluation. Both algorithms showed promising results and as none clearly outperformed the other we can conclude that both would be good candidates for further development. For the rule-based algorithm more advanced rules, especially ones that could incorporate some semantic knowledge, was identified as the most important avenue of improvement. For the machine learning algorithm more training data would likely be the most beneficial. For both algorithms improved detection of mention spans would also help, as this was identified as one of the most error-prone components.