Communicative-Function-Based Sentence Classification for Construction of an Academic Formulaic Expression Database

Formulaic expressions (FEs), such as {`}in this paper, we propose{'} are frequently used in scientific papers. FEs convey a communicative function (CF), i.e. {`}showing the aim of the paper{'} in the above-mentioned example. Although CF-labelled FEs are helpful in assisting academic writing, the construction of FE databases requires manual labour for assigning CF labels. In this study, we considered a fully automated construction of a CF-labelled FE database using the top{--}down approach, in which the CF labels are first assigned to sentences, and then the FEs are extracted. For the CF-label assignment, we created a CF-labelled sentence dataset, on which we trained a SciBERT classifier. We show that the classifier and dataset can be used to construct FE databases of disciplines that are different from the training data. The accuracy of in-disciplinary classification was more than 80{\%}, while cross-disciplinary classification also worked well. We also propose an FE extraction method, which was applied to the CF-labelled sentences. Finally, we constructed and published a new, large CF-labelled FE database. The evaluation of the final CF-labelled FE database showed that approximately 65{\%} of the FEs are correct and useful, which is sufficiently high considering practical use.