This paper presents a work in progress to create a multilayered syntactically and semantically annotated text corpus for Latvian. The broad application area we address is natural language understanding (NLU), while more specific applications are abstractive text summarization and knowledge base population, which are required by the project industrial partner, Latvian information agency LETA, for the automation of various media monitoring processes. Both the multilayered corpus and the downstream applications are anchored in cross-lingual state-of-the-art representations: Universal Dependencies (UD), FrameNet, PropBank and Abstract Meaning Representation (AMR). In this paper, we particularly focus on the consecutive annotation of the treebank and framebank layers. We also draw links to the ultimate AMR layer and the auxiliary named entity and coreference annotation layers. Since we are aiming at a medium-sized still general-purpose corpus for a less-resourced language, an important aspect we consider is the variety and balance of the corpus in terms of genres, authors and lexical units.
@InProceedings{GRUZITIS18.935, author = {Normunds Gruzitis and Lauma Pretkalnina and Baiba Saulite and Laura Rituma and Gunta Nespore-Berzkalne and Arturs Znotins and Peteris Paikens}, title = "{Creation of a Balanced State-of-the-Art Multilayer Corpus for NLU}", booktitle = {Proceedings of the Eleventh International Conference on Language Resources and Evaluation (LREC 2018)}, year = {2018}, month = {May 7-12, 2018}, address = {Miyazaki, Japan}, editor = {Nicoletta Calzolari (Conference chair) and Khalid Choukri and Christopher Cieri and Thierry Declerck and Sara Goggi and Koiti Hasida and Hitoshi Isahara and Bente Maegaard and Joseph Mariani and Hélène Mazo and Asuncion Moreno and Jan Odijk and Stelios Piperidis and Takenobu Tokunaga}, publisher = {European Language Resources Association (ELRA)}, isbn = {979-10-95546-00-9}, language = {english} }
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