2020 CONLL CoNLL 2020

HIT-SCIR at MRP 2020: Transition-based Parser and Iterative Inference Parser

Abstract

AbstractThis paper describes our submission system (HIT-SCIR) for the CoNLL 2020 shared task: Cross-Framework and Cross-Lingual Meaning Representation Parsing. The task includes five frameworks for graph-based meaning representations, i.e., UCCA, EDS, PTG, AMR, and DRG. Our solution consists of two sub-systems: transition-based parser for Flavor (1) frameworks (UCCA, EDS, PTG) and iterative inference parser for Flavor (2) frameworks (DRG, AMR). In the final evaluation, our system is ranked 3rd among the seven team both in Cross-Framework Track and Cross-Lingual Track, with the macro-averaged MRP F1 score of 0.81/0.69.

🌉 Interdisciplinary Bridge — Machine Learning and Natural Language Processing
🧭 Keyword Pioneer — iterative inference parser
🐝 Cross-Pollinator — Artificial Intelligence, Computer Science, Deep Learning, Interdisciplinary, Machine Learning, Natural Language Processing