5 papers · 1 filter
Probabilistic, Structure-Aware Algorithms for Improved Variety, Accuracy, and Coverage of AMR Alignments
Austin Blodgett, Nathan Schneider
We present algorithms for aligning components of Abstract Meaning Representation (AMR) graphs to spans in English sentences. We leverage unsupervised learning in combination with h…
Transition-based Parsing with Stack-Transformers
Ramon Fernandez Astudillo, Miguel Ballesteros, Tahira Naseem +2
Modeling the parser state is key to good performance in transition-based parsing. Recurrent Neural Networks considerably improved the performance of transition-based systems by mod…
An Improved Approach for Semantic Graph Composition with CCG
Austin Blodgett, Nathan Schneider
This paper builds on previous work using Combinatory Categorial Grammar (CCG) to derive a transparent syntax-semantics interface for Abstract Meaning Representation (AMR) parsing.…
Adpositional Supersenses for Mandarin Chinese
Yilun Zhu, Yang Liu, Siyao Peng +3
This study adapts Semantic Network of Adposition and Case Supersenses (SNACS) annotation to Mandarin Chinese and demonstrates that the same supersense categories are appropriate fo…
Comprehensive Supersense Disambiguation of English Prepositions and Possessives
Nathan Schneider, Jena D. Hwang, Vivek Srikumar +6
Semantic relations are often signaled with prepositional or possessive marking--but extreme polysemy bedevils their analysis and automatic interpretation. We introduce a new annota…