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Neural amr: Sequence-to-sequence models for parsing and generation
Sequence-to-sequence models have shown strong performance across a broad range of
applications. However, their application to parsing and generating text usingAbstract …
applications. However, their application to parsing and generating text usingAbstract …
AMR parsing as sequence-to-graph transduction
We propose an attention-based model that treats AMR parsing as sequence-to-graph
transduction. Unlike most AMR parsers that rely on pre-trained aligners, external semantic …
transduction. Unlike most AMR parsers that rely on pre-trained aligners, external semantic …
Neural semantic parsing by character-based translation: Experiments with abstract meaning representations
We evaluate the character-level translation method for neural semantic parsing on a large
corpus of sentences annotated with Abstract Meaning Representations (AMRs). Using a …
corpus of sentences annotated with Abstract Meaning Representations (AMRs). Using a …
[PDF][PDF] Semeval-2016 task 8: Meaning representation parsing
J May - Proceedings of the 10th international workshop on …, 2016 - aclanthology.org
In this report we summarize the results of the SemEval 2016 Task 8: Meaning
Representation Parsing. Participants were asked to generate Abstract Meaning …
Representation Parsing. Participants were asked to generate Abstract Meaning …
[PDF][PDF] One Model to Rule them all
J Bjerva - Multitask and Multilingual Modelling for Lexical …, 2017 - research.rug.nl
University of Groningen One Model to Rule them All Bjerva, Johannes Page 1 University of
Groningen One Model to Rule them All Bjerva, Johannes IMPORTANT NOTE: You are advised …
Groningen One Model to Rule them All Bjerva, Johannes IMPORTANT NOTE: You are advised …
TUPA at MRP 2019: A multi-task baseline system
This paper describes the TUPA system submission to the shared task on Cross-Framework
Meaning Representation Parsing (MRP) at the 2019 Conference for Computational …
Meaning Representation Parsing (MRP) at the 2019 Conference for Computational …
One model to rule them all: Multitask and multilingual modelling for lexical analysis
J Bjerva - arxiv preprint arxiv:1711.01100, 2017 - arxiv.org
When learning a new skill, you take advantage of your preexisting skills and knowledge. For
instance, if you are a skilled violinist, you will likely have an easier time learning to play …
instance, if you are a skilled violinist, you will likely have an easier time learning to play …
Automatic accuracy prediction for AMR parsing
Meaning Representation (AMR) represents sentences as directed, acyclic and rooted
graphs, aiming at capturing their meaning in a machine readable format. AMR parsing …
graphs, aiming at capturing their meaning in a machine readable format. AMR parsing …
[PDF][PDF] Parsing and Generation for the Abstract Meaning Representation
J Flanigan - 2018 - jflanigan.github.io
A key task in intelligent language processing is obtaining semantic representations that
abstract away from surface lexical and syntactic decisions. The Abstract Meaning …
abstract away from surface lexical and syntactic decisions. The Abstract Meaning …
The meaning factory at semeval-2017 task 9: Producing amrs with neural semantic parsing
We evaluate a semantic parser based on a character-based sequence-to-sequence model
in the context of the SemEval-2017 shared task on semantic parsing for AMRs. With data …
in the context of the SemEval-2017 shared task on semantic parsing for AMRs. With data …