Year: 2015
Type: preprint
Abstract: In this paper I explain the reasons that led me to research and conceive a novel technology for dependency parsing, mixing together the strengths of data-driven transition-based and constraint-based approaches. In particular I highlight the problem to infer the reliability of the results of a data-driven transition-based parser, which is extremely important for high-level processes that expect to use correct parsing results. I then briefly introduce a number of notes about a new parser model I'm working on, capable to proceed with the analysis in a "more aware" way, with a more "robust" concept of robustness.
Source: arXiv (Cornell University)
Author: Grella, Matteo
Language: English
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
Funder: Università degli Studi di Torino
OpenAlex ID: W2284945930