Abstract
Abstract Meaning Representation (AMR), an annotation scheme for natural language semantics, has drawn attention for its simplicity and representational power. Because AMR annotations are not designed for human readability, we present AMRICA, a visual aid for exploration of AMR annotations. AMRICA can visualize an AMR or the difference between two AMRs to help users diagnose interannotator disagreement or errors from an AMR parser. AMRICA can also automatically align and visualize the AMRs of a sentence and its translation in a parallel text. We believe AMRICA will simplify and streamline exploratory research on cross-lingual AMR corpora.Meaning Representation (AMR), an annotation scheme for natural language semantics, has drawn attention for its simplicity and representational power. Because AMR annotations are not designed for human readability, we present AMRICA, a visual aid for exploration of AMR annotations. AMRICA can visualize an AMR or the difference between two AMRs to help users diagnose interannotator disagreement or errors from an AMR parser. AMRICA can also automatically align and visualize the AMRs of a sentence and its translation in a parallel text. We believe AMRICA will simplify and streamline exploratory research on cross-lingual AMR corpora.
Highlights
Research in statistical machine translation has begun to turn to semantics
Effective semantics-based translation systems pose a crucial need for a practical cross-lingual semantic representation
AMRICA does not distinguish between constants and variables, since their labels tend to be grounded in the words of the sentence, which it uses for alignment
Summary
Effective semantics-based translation systems pose a crucial need for a practical cross-lingual semantic representation. One such schema, Abstract Meaning Representation (AMR; Banarescu et al, 2013), has attracted attention for its simplicity and expressive power. AMR represents the meaning of a sentence as a directed graph over concepts representing entities, events, and properties like names or quantities. AMRICA can visualize differences between aligned AMRs of a sentence, enabling users to diagnose differences in multiple annotations or between an annotation and an automatic AMR parse (Section 2). To aid researchers studying crosslingual semantics, AMRICA can visualize differences between the AMR of a sentence and that of its translation (Section 3) using a novel cross-lingual extension to Smatch (Cai and Knight, 2013). The AMRICA code and a tutorial are publicly available.
Sign-in/Register to view highlights & summary 
Published Version (
Free)
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
