The parse is darc and full of errors: Universal dependency parsing with transition-based and graph-based algorithms
Year: 2017
Type: conference-paper
Abstract: We developed two simple systems for dependency parsing: darc, a transition-based parser, and mstnn, a graph-based parser.We tested our systems in the CoNLL 2017 UD Shared Task, with darc being the official system.Darc ranked 12 th among 33 systems, just above the baseline.Mstnn had no official ranking, but its main score was above the 27 th .In this paper, we describe our two systems, examine their strengths and weaknesses, and discuss the lessons we learned.
DOI: 10.18653/v1/k17-3013
Institution: University of Tübingen
Language: English
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: gold
OpenAlex ID: W2740805311