Abstract
This paper concentrates on the study of multiword expressions related to grammatical collocations. We propose a method to automatically extract grammatical collocations from a corpus. Our method involves selecting collocations in line with certain structure based on part of speech information and analyses of base phrases, extracting meaningful grammatical collocations by statistical analysis of associativity. In addition to statistics and linguistic knowledge, we also rely on syntactic patterns of multiword expressions. Take the collocate pattern of (“at”, “cost”) for example. Pattern of seed MWEs will enable us to obtain multiword expressions like “at cost” or “at all costs”. We exploit mutual information (MI) to evaluate each collocation candidate and filter out ones with low mutual information rate, which is a threshold trained on real data. Collocations with MI higher than the lower-bound are further used to assist in the extraction of multiword expressions. The grammatical collocations and related multiword expressions can be used in many Natural Language Processing applications, including computer assisted language learning, parsing, and machine translation.