FrameNet and frame semantics have proved useful for a number of natural language processing (NLP) tasks. However, in this connection FrameNet has often been criticized for its limited coverage. A proposed limited-effort solution to this problem is to develop domainspecific (sublanguage) framenets to complement the general-language FrameNet for particular NLP tasks, and in the literature we find such initiatives covering, e.g., medicine, soccer, and tourism. In this paper, we report on our experiments and first results on building a framenet to cover the terms and concepts encountered in descriptive linguistic grammars. A contextual statistics based approach is used to judge the polysemous nature of domain-specific terms, and to design new domain-specific frames. The work is part of a more extensive research undertaking where we are developing NLP methodologies for automatic extraction of linguistic information from traditional linguistic descriptions to build typological databases, which otherwise are populated using a labor intensive manual process.
@InProceedings{MALM18.10, author = {Per Malm ,Shafqat Mumtaz Virk ,Lars Borin and Anju Saxena}, title = {LingFN: Towards a Domain-specific Linguistic FrameNet}, booktitle = {Proceedings of the Eleventh International Conference on Language Resources and Evaluation (LREC 2018)}, year = {2018}, month = {may}, date = {7-12}, location = {Miyazaki, Japan}, editor = {Tiago Timponi Torrent and Lars Borin and Collin F. Baker}, publisher = {European Language Resources Association (ELRA)}, address = {Paris, France}, isbn = {979-10-95546-04-7}, language = {english} }
Summary of the paper