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AMR Parsing as Sequence-to-Graph Transduction
[article]
2019
arXiv
pre-print
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We propose an attention-based model that treats AMR parsing as sequence-to-graph transduction. ...
of labeled AMR data. ...
Government is authorized to reproduce and distribute reprints for Governmental purposes. ...
arXiv:1905.08704v2
fatcat:w2tdvlo6hvc65phutke32t7j4a
Broad-Coverage Semantic Parsing as Transduction
[article]
2019
arXiv
pre-print
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We unify different broad-coverage semantic parsing tasks under a transduction paradigm, and propose an attention-based neural framework that incrementally builds a meaning representation via a sequence ...
Experiments conducted on three separate broad-coverage semantic parsing tasks -- AMR, SDP and UCCA -- demonstrate that our attention-based neural transducer improves the state of the art on both AMR and ...
Government is authorized to reproduce and distribute reprints for Governmental purposes. ...
arXiv:1909.02607v2
fatcat:enhzznavwfeztdzm4ddpxxx7my
AMR Parsing via Graph-Sequence Iterative Inference
[article]
2020
arXiv
pre-print
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We propose a new end-to-end model that treats AMR parsing as a series of dual decisions on the input sequence and the incrementally constructed graph. ...
in the output graph to construct the new concept. ...
Seq2seq-based parsing (Barzdins and Gosko, 2016; Konstas et al., 2017; van Noord and Bos, 2017; Peng et al., 2018) views parsing as sequence-to-sequence transduction by some linearization of the AMR ...
arXiv:2004.05572v2
fatcat:levfg6nhzvgydbghluqaqzo2fa
Broad-Coverage Semantic Parsing as Transduction
2019
Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP)
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We unify different broad-coverage semantic parsing tasks under a transduction paradigm, and propose an attention-based neural framework that incrementally builds a meaning representation via a sequence ...
Experiments conducted on three separate broadcoverage semantic parsing tasks -AMR, SDP and UCCA -demonstrate that our attentionbased neural transducer improves the state of the art on both AMR and UCCA ...
Government is authorized to reproduce and distribute reprints for Governmental purposes. ...
doi:10.18653/v1/d19-1392
dblp:conf/emnlp/ZhangMDD19
fatcat:gzndqwnxxfbtdellsdjnyozya4
Levi Graph AMR Parser using Heterogeneous Attention
[article]
2021
arXiv
pre-print
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Coupled with biaffine decoders, transformers have been effectively adapted to text-to-graph transduction and achieved state-of-the-art performance on AMR parsing. ...
This paper presents a novel approach to AMR parsing by combining heterogeneous data (tokens, concepts, labels) as one input to a transformer to learn attention, and use only attention matrices from the ...
3.1 Text-to-Graph Transducer Figure 1 shows the overview of our Text-to-Graph Transduction model. ...
arXiv:2107.04152v1
fatcat:245h5dumffbvdbjd37q7swo2cq
One SPRING to Rule Them Both: Symmetric AMR Semantic Parsing and Generation without a Complex Pipeline
2021
Zenodo
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In contrast, state-of-the-art AMR-to-Text generation, which can be seen as the inverse to parsing, is based on simpler seq2seq. ...
In this paper, we cast Text-toAMR and AMR-to-Text as a symmetric transduction task and show that by devising a careful graph linearization and extending a pretrained encoder-decoder model, it is possible ...
Text-to-AMR Parsing Pure seq2seq Seq2seq approaches model Text-to-AMR parsing as a transduction of the sentence into a linearization of the AMR graph. ...
doi:10.5281/zenodo.5543380
fatcat:j7chtyqzn5hdledgcwpnnogdda
Making Better Use of Bilingual Information for Cross-Lingual AMR Parsing
[article]
2021
arXiv
pre-print
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However, they find that concepts in their predicted AMR graphs are less specific. We argue that the misprediction of concepts is due to the high relevance between English tokens and AMR concepts. ...
In this work, we introduce bilingual input, namely the translated texts as well as non-English texts, in order to enable the model to predict more accurate concepts. ...
., 2020) , we treat crosslingual AMR parsing as a sequence-to-sequence transduction problem and improve seq2seq models with bilingual input and auxiliary task. ...
arXiv:2106.04814v1
fatcat:jppfrhdupnhdfmrlrgqvrile2m
Graph Pre-training for AMR Parsing and Generation
[article]
2022
arXiv
pre-print
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Recently, pre-trained language models (PLMs) have advanced tasks of AMR parsing and AMR-to-text generation, respectively. ...
We further design a unified framework to bridge the gap between pre-training and fine-tuning tasks. Experiments on both AMR parsing and AMR-to-text generation show the superiority of our model. ...
We would like to thank anonymous reviewers for their insightful comments. ...
arXiv:2203.07836v4
fatcat:e5gq5h4jyfdgxdmz77czf7hhlq
Universal Decompositional Semantic Parsing
[article]
2020
arXiv
pre-print
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We introduce a transductive model for parsing into Universal Decompositional Semantics (UDS) representations, which jointly learns to map natural language utterances into UDS graph structures and annotate ...
We also introduce a strong pipeline model for parsing into the UDS graph structure, and show that our transductive parser performs comparably while additionally performing attribute prediction. ...
The views and conclusions expressed herein are those of the authors and should not be interpreted as representing official policies or endorsements of DARPA, IARPA, or the U.S. Government. ...
arXiv:1910.10138v3
fatcat:z7vava7ljfhudmejey4ann762m
Neural AMR: Sequence-to-Sequence Models for Parsing and Generation
[article]
2017
arXiv
pre-print
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We present extensive ablative and qualitative analysis including strong evidence that sequence-based AMR models are robust against ordering variations of graph-to-sequence conversions. ...
of the AMR graphs. ...
We define a linearization order for an AMR graph as any sequence of its nodes and edges. ...
arXiv:1704.08381v3
fatcat:oupyiqgmwzbbtnvw64tpuhgsuu
Neural AMR: Sequence-to-Sequence Models for Parsing and Generation
2017
Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
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of the AMR graphs. ...
We present extensive ablative and qualitative analysis including strong evidence that sequencebased AMR models are robust against ordering variations of graph-to-sequence conversions. 157 ...
Conclusions We applied sequence-to-sequence models to the tasks of AMR parsing and AMR generation, by carefully preprocessing the graph representation and scaling our models via pretraining on millions ...
doi:10.18653/v1/p17-1014
dblp:conf/acl/KonstasIYCZ17
fatcat:l6kw32l2evg6nl55obver3s6zq
AMR Parsing using Stack-LSTMs
[article]
2017
arXiv
pre-print
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We present a transition-based AMR parser that directly generates AMR parses from plain text. We use Stack-LSTMs to represent our parser state and make decisions greedily. ...
Adding additional information, such as POS tags and dependency trees, improves the results further. ...
We implemented an oracle that produces the sequence of actions that leads to the gold (or close to gold) AMR graph. ...
arXiv:1707.07755v2
fatcat:y7zx5kb3ljgsxikkd3xaajds6i
AMR Parsing using Stack-LSTMs
2017
Proceedings of the 2017 Conference on Empirical Methods in Natural Language Processing
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We present a transition-based AMR parser that directly generates AMR parses from plain text. We use Stack-LSTMs to represent our parser state and make decisions greedily. ...
Adding additional information, such as POS tags and dependency trees, improves the results further. ...
We implemented an oracle that produces the sequence of actions that leads to the gold (or close to gold) AMR graph. ...
doi:10.18653/v1/d17-1130
dblp:conf/emnlp/BallesterosA17
fatcat:ybe32z5ebzbzrk2isnq7ibdzpm
ShanghaiTech at MRP 2019: Sequence-to-Graph Transduction with Second-Order Edge Inference for Cross-Framework Meaning Representation Parsing
[article]
2020
arXiv
pre-print
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This paper presents the system used in our submission to the CoNLL 2019 shared task: Cross-Framework Meaning Representation Parsing. ...
Our system is a graph-based parser which combines an extended pointer-generator network that generates nodes and a second-order mean field variational inference module that predicts edges. ...
Lemma and Named Entity Tags
Conclusion In this paper, we present our graph-based parsing system for MRP 2019, which combines two state-of-the-art methods for sequence to graph node generation and second-order ...
arXiv:2004.03849v1
fatcat:653vdmfi35dhnmx2ujaibc6odu
Ensembling Graph Predictions for AMR Parsing
[article]
2022
arXiv
pre-print
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For example, in natural language processing, it is very common to parse texts into dependency trees or abstract meaning representation (AMR) graphs. ...
As the problem is NP-Hard, we propose an efficient heuristic algorithm to approximate the optimal solution. To validate our approach, we carried out experiments in AMR parsing problems. ...
Cai&Lam The model proposed in [Cai and Lam, 2020b] treats AMR parsing as a series of dual decisions (i.e., which parts of the sequence to abstract, and where in the graph to construct) on the input sequence ...
arXiv:2110.09131v2
fatcat:5jhi7fvasrgrpf226vwf6743mi
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