CUNY-PKU Parser at SemEval-2019 Task 1: Cross-Lingual Semantic Parsing with UCCA

Abstract

This paper describes the systems of the CUNY-PKU team in "SemEval 2019 Task 1: Cross-lingual Semantic Parsing with UCCA" 1. We introduce a novel method by applying a cascaded MLP and BiLSTM model. Then, we ensemble multiple system-outputs by reparsing. Our system won the second places in German-20K-Closed track, and third place in English-20K-Closed track.

A Siamese Neural Network for Learning Semantically-Informed Sentence Embeddings

“…Current UCCA-based semantic parsers can be categorised based on their approaches as follows: (i) transition-based (Hershcovich et al, 2017;Pütz & Glocker, 2019;Lyu et al, 2019), (ii) graph-based (Cao et al, 2019;Droganova et al, 2019;Koreeda et al, 2019;Li et al, 2019;Na et al, 2019;Wang et al, 2019a;Zhang et al, 2019) , (iii) composition-based (Che et al;Donatelli et al, 2019;Oepen & Flickinger, 2019), and (iv) encoder-decoder based (Dou et al, 2020;Na & Min, 2020;Cai & Lam, 2020).…”

“…Transition-based approaches (Bai & Zhao, 2019;Che et al;Lai et al, 2019;Straka & Straková, 2019) define a sequence of actions that eventually build semantic graphs. Some of the transition-based approaches extend the models by adding extra actions (Arviv et al, 2020;Lai et al, 2019), adding new features (Pütz & Glocker, 2019;Bai & Zhao, 2019), or layers (Lyu et al, 2019;Che et al).…”

XL-AMR: Enabling Cross-Lingual AMR Parsing with Transfer Learning Techniques

“…Besides AMR, various different formalisms have been proposed over the years to encode semantic structures: Elementary Dependency Structures (Oepen and Lønning, 2006, EDS), Prague Tectogrammatical Graphs (Hajič et al, 2012, PTG), Universal Conceptual Cognitive Annotation (Abend and Rappoport, 2013, UCCA), Universal Decompositional Semantics (White et al, 2016, UDS), inter alia. While some frameworks, such as UCCA and UDS, have been exploited in a cross-linguistic setting (Lyu et al, 2019;Zhang et al, 2018), cross-lingual AMR has mainly been studied within the scope of annotation analysis works (Xue et al, 2014;. These works point out the limitations of AMR as an interlingua, and consider them partly due to the distinctions in the underlying ontologies and structural divergences among languages.…”

Cross-lingual Semantic Representation for NLP with UCCA

“…The tutorial will describe the guidelines and rationale behind UCCA, helping potential application designers understand what abstractions it makes. Significant effort has been devoted to building UCCA parsers (Hershcovich et al, 2017;Hershcovich et al, 2018;Jiang et al, 2019;Lyu et al, 2019;Tuan Nguyen and Tran, 2019;Taslimipoor et al, 2019;Marzinotto et al, 2019;Pütz and Glocker, 2019;Yu and Sagae, 2019;Zhang et al, 2019a;Hershcovich and Arviv, 2019;Donatelli et al, 2019;Che et al, 2019;Bai and Zhao, 2019;Lai et al, 2019;Koreeda et al, 2019;Straka and Straková, 2019;Cao et al, 2019;Zhang et al, 2019b;Droganova et al, 2019;Chen et al, 2019;Arviv et al, 2020;Samuel and Straka, 2020;Dou et al, 2020), including a SemEval 2019 shared task on cross-lingual UCCA parsing (Hershcovich et al, 2019b), which had 8 participating teams, as well as CoNLL 2019 and CoNLL 2020 shared tasks on cross-framework and cross-lingual meaning representation parsing Oepen et al, 2020), where 12 and 4 teams, respectively, submitted parsed UCCA graphs. This tutorial will allow researchers interested in UCCA parsing, and more generally graph parsing, deepen their understanding of the framework, and what properties make it unique.…”