1 code implementation • EACL (GWC) 2021 • John P. McCrae, Michael Wayne Goodman, Francis Bond, Alexandre Rademaker, Ewa Rudnicka, Luis Morgado Da Costa
The Global Wordnet Formats have been introduced to enable wordnets to have a common representation that can be integrated through the Global WordNet Grid.
no code implementations • EACL (GWC) 2021 • Michael Wayne Goodman, Francis Bond
This paper introduces Wn, a new Python library for working with wordnets.
1 code implementation • ACL 2020 • Michael Wayne Goodman
Abstract Meaning Representation (AMR) (Banarescu et al., 2013) is a framework for semantic dependencies that encodes its rooted and directed acyclic graphs in a format called PENMAN notation.
no code implementations • LREC 2020 • Francis Bond, Luis Morgado da Costa, Michael Wayne Goodman, John Philip McCrae, Ahti Lohk
In this paper we discuss the experience of bringing together over 40 different wordnets.
2 code implementations • 4 Sep 2019 • Michael Wayne Goodman
Meaning Representation (AMR; Banarescu et al., 2013) encodes the meaning of sentences as a directed graph and Smatch (Cai and Knight, 2013) is the primary metric for evaluating AMR graphs.
no code implementations • LREC 2016 • Ann Copestake, Guy Emerson, Michael Wayne Goodman, Matic Horvat, Alex Kuhnle, er, Ewa Muszy{\'n}ska
We describe resources aimed at increasing the usability of the semantic representations utilized within the DELPH-IN (Deep Linguistic Processing with HPSG) consortium.
no code implementations • LREC 2014 • Fei Xia, William Lewis, Michael Wayne Goodman, Joshua Crowgey, Emily M. Bender
In this paper, we describe the expansion of the ODIN resource, a database containing many thousands of instances of Interlinear Glossed Text (IGT) for over a thousand languages harvested from scholarly linguistic papers posted to the Web.