Building robust natural language understanding systems will require a clear characterization of whether and how various linguistic meaning representations complement each other. To perform a systematic comparative analysis, we evaluate the mapping between meaning representations from different frameworks using two complementary methods: (i) a rule-based converter, and (ii) a supervised delexicalized parser that parses to one framework using only information from the other as features. We apply these methods to convert the STREUSLE corpus (with syntactic and lexical semantic annotations) to UCCA (a graph-structured full-sentence meaning representation). Both methods yield surprisingly accurate target representations, close to fully supervised UCCA parser quality—indicating that UCCA annotations are partially redundant with STREUSLE annotations. Despite this substantial convergence between frameworks, we find several important areas of divergence.
|Original language||American English|
|Title of host publication||COLING 2020 - 28th International Conference on Computational Linguistics, Proceedings of the Conference|
|Editors||Donia Scott, Nuria Bel, Chengqing Zong|
|Publisher||Association for Computational Linguistics (ACL)|
|Number of pages||20|
|State||Published - 2020|
|Event||28th International Conference on Computational Linguistics, COLING 2020 - Virtual, Online, Spain|
Duration: 8 Dec 2020 → 13 Dec 2020
|Name||COLING 2020 - 28th International Conference on Computational Linguistics, Proceedings of the Conference|
|Conference||28th International Conference on Computational Linguistics, COLING 2020|
|Period||8/12/20 → 13/12/20|
Bibliographical noteFunding Information:
This research was supported in part by grant 2016375 from the United States–Israel Binational Science Foundation (BSF), Jerusalem, Israel. ML is funded by a Google Focused Research Award. We acknowledge the computational resources provided by CSC in Helsinki and Sigma2 in Oslo through NeIC-NLPL (www.nlpl.eu).
© 2020 COLING 2020 - 28th International Conference on Computational Linguistics, Proceedings of the Conference. All rights reserved.
- natural language understanding
- Computational Linguistics