A survey of syntactic-semantic parsing based on constituent and dependency structures
MS Zhang - Science China Technological Sciences, 2020 - Springer
Syntactic and semantic parsing has been investigated for decades, which is one primary
topic in the natural language processing community. This article aims for a brief survey on …
topic in the natural language processing community. This article aims for a brief survey on …
Fast and accurate neural CRF constituency parsing
Estimating probability distribution is one of the core issues in the NLP field. However, in both
deep learning (DL) and pre-DL eras, unlike the vast applications of linear-chain CRF in …
deep learning (DL) and pre-DL eras, unlike the vast applications of linear-chain CRF in …
Biomedical event extraction as sequence labeling
A Ramponi, R Van Der Goot… - Proceedings of the …, 2020 - aclanthology.org
Abstract We introduce Biomedical Event Extraction as Sequence Labeling (BeeSL), a joint
end-to-end neural information extraction model. BeeSL recasts the task as sequence …
end-to-end neural information extraction model. BeeSL recasts the task as sequence …
Bottom-up constituency parsing and nested named entity recognition with pointer networks
Constituency parsing and nested named entity recognition (NER) are similar tasks since
they both aim to predict a collection of nested and non-crossing spans. In this work, we cast …
they both aim to predict a collection of nested and non-crossing spans. In this work, we cast …
Parsing as pretraining
Recent analyses suggest that encoders pretrained for language modeling capture certain
morpho-syntactic structure. However, probing frameworks for word vectors still do not report …
morpho-syntactic structure. However, probing frameworks for word vectors still do not report …
On the use of parsing for named entity recognition
Parsing is a core natural language processing technique that can be used to obtain the
structure underlying sentences in human languages. Named entity recognition (NER) is the …
structure underlying sentences in human languages. Named entity recognition (NER) is the …
Structure-unified m-tree coding solver for mathword problem
As one of the challenging NLP tasks, designing math word problem (MWP) solvers has
attracted increasing research attention for the past few years. In previous work, models …
attracted increasing research attention for the past few years. In previous work, models …
Distilling neural networks for greener and faster dependency parsing
M Anderson, C Gómez-Rodríguez - arXiv preprint arXiv:2006.00844, 2020 - arxiv.org
The carbon footprint of natural language processing research has been increasing in recent
years due to its reliance on large and inefficient neural network implementations. Distillation …
years due to its reliance on large and inefficient neural network implementations. Distillation …
N-ary constituent tree parsing with recursive semi-Markov model
X Xin, J Li, Z Tan - Proceedings of the 59th Annual Meeting of the …, 2021 - aclanthology.org
In this paper, we study the task of graph-based constituent parsing in the setting that
binarization is not conducted as a pre-processing step, where a constituent tree may consist …
binarization is not conducted as a pre-processing step, where a constituent tree may consist …
Sequence labeling parsing by learning across representations
We use parsing as sequence labeling as a common framework to learn across constituency
and dependency syntactic abstractions. To do so, we cast the problem as multitask learning …
and dependency syntactic abstractions. To do so, we cast the problem as multitask learning …