Extracting Semantic Frames using hfst-pmatch

We use hfst-pmatch (Lindén et al., 2013), a pattern-matching tool mimicking and extending Xerox fst (Karttunen, 2011), for demonstrating how to develop a semantic frame extractor. We select a FrameNet (Baker et al., 1998) frame and write shallowly syntactic pattern-matching rules based on part-of-speech information and morphology from either a morphological automaton or tagged text.Peer reviewe

Using HFST—Helsinki Finite-State Technology for Recognizing Semantic Frames

To recognize semantic frames in languages with a rich morphology, we need computational morphology. In this paper, we look at one particular framework, HFST–Helsinki Finite-State Technology, and how to use it for recognizing semantic frames in context. HFST enables tokenization, morphological analysis, tagging, and frame annotation in one single framework.Peer reviewe

Border crossing and trespassing? : Expanding digital humanities research to developing peripheries with the novel digital technologies

Peer reviewe

Wanca in Korp : Text corpora for underresourced Uralic languages

Peer reviewe

Proceedings of the Research Data And Humanities (RDHUM) 2019 Conference: Data, Methods And Tools

Analytical bibliography aims to understand the production of books. Systematic methods can be used to determine an overall view of the publication history. In this paper, we present the state of the art analytical approach towards the determination of editions using the ESTC meta data. The preliminary results illustrate that metadata cleanup and analysis can provide opportunities for edition determination. This would significantly help projects aiming to do large scale text mining.</p

Digital Histories

Historical scholarship is currently undergoing a digital turn. All historians have experienced this change in one way or another, by writing on word processors, applying quantitative methods on digitalized source materials, or using internet resources and digital tools. Digital Histories showcases this emerging wave of digital history research. It presents work by historians who – on their own or through collaborations with e.g. information technology specialists – have uncovered new, empirical historical knowledge through digital and computational methods. The topics of the volume range from the medieval period to the present day, including various parts of Europe. The chapters apply an exemplary array of methods, such as digital metadata analysis, machine learning, network analysis, topic modelling, named entity recognition, collocation analysis, critical search, and text and data mining. The volume argues that digital history is entering a mature phase, digital history ‘in action’, where its focus is shifting from the building of resources towards the making of new historical knowledge. This also involves novel challenges that digital methods pose to historical research, including awareness of the pitfalls and limitations of the digital tools and the necessity of new forms of digital source criticisms. Through its combination of empirical, conceptual and contextual studies, Digital Histories is a timely and pioneering contribution taking stock of how digital research currently advances historical scholarship