It has been exactly a decade since the first establishment of SPMRL, a research initiative unifying multiple research efforts to address the peculiar challenges of Statistical Parsing for Morphologically-Rich Languages (MRLs). Here we reflect on parsing MRLs in that decade, highlight the solutions and lessons learned for the architectural, modeling and lexical challenges in the pre-neural era, and argue that similar challenges re-emerge in neural architectures for MRLs. We then aim to offer a climax, suggesting that incorporating symbolic ideas proposed in SPMRL terms into nowadays neural architectures has the potential to push NLP for MRLs to a new level. We sketch a strategies for designing Neural Models for MRLs (NMRL), and showcase preliminary support for these strategies via investigating the task of multi-tagging in Hebrew, a morphologically-rich, high-fusion, language.
|Title of host publication||ACL 2020 - 58th Annual Meeting of the Association for Computational Linguistics, Proceedings of the Conference|
|Publisher||Association for Computational Linguistics (ACL)|
|Number of pages||13|
|State||Published - 2020|
|Event||58th Annual Meeting of the Association for Computational Linguistics, ACL 2020 - Virtual, Online, United States|
Duration: 5 Jul 2020 → 10 Jul 2020
|Name||Proceedings of the Annual Meeting of the Association for Computational Linguistics|
|Conference||58th Annual Meeting of the Association for Computational Linguistics, ACL 2020|
|Period||5/07/20 → 10/07/20|
Bibliographical noteFunding Information:
We thank Clara Vania, Adam Lopez, and members of the Edinburgh-NLP seminar, Yoav Goldberg, Ido Dagan, and members of the BIU-NLP seminar, for intriguing discussions on earlier presentations of this work. This research is kindly supported by the Israel Science Foundation (ISF), grant No. 1739/16, and by the European Research Council (ERC), under the Europoean Union Horizon 2020 research and innovation programme, grant No. 677352.
© 2020 Association for Computational Linguistics