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Increasing NLP Parsing Efficiency with Chunking
(M D P I AG, 2018-09-19)
[Abstract] We introduce a “Chunk-and-Pass” parsing technique influenced by a psycholinguistic model, where linguistic information is processed not word-by-word but rather in larger chunks of words. We present preliminary ...
Towards fast natural language parsing: FASTPARSE ERC Starting Grant
(Sociedad Española para el Procesamiento del Lenguaje Natural (SEPLN), 2017-09)
[Abstract:] The goal of the FASTPARSE project (Fast Natural Language Parsing for
Large-Scale NLP), funded by the European Research Council (ERC), is to achieve
a breakthrough in the speed of natural language syntactic ...
Viable Dependency Parsing as Sequence Labeling
(Association for Computational Linguistics (ACL), 2019-06)
[Abstract]: We recast dependency parsing as a sequence labeling problem, exploring several encodings of dependency trees as labels. While dependency parsing by means of sequence labeling had been attempted in existing work, ...
A non-projective greedy dependency parser with bidirectional LSTMs
(Association for Computational Linguistics, 2017-08)
[Abstract]: The LyS-FASTPARSE team present BIST-COVINGTON, a neural implementation of the Covington (2001) algorithm for non-projective dependency parsing. The bidirectional LSTM approach by Kiperwasser and Goldberg (2016) ...
Multitask Pointer Network for Multi-Representational Parsing
(Elsevier, 2022-01-25)
[Abstract] Dependency and constituent trees are widely used by many artificial intelligence applications for representing the syntactic structure of human languages. Typically, these structures are separately produced by ...
Dependency parsing with bottom-up Hierarchical Pointer Networks
(Elsevier, 2023-03)
[Abstract] Dependency parsing is a crucial step towards deep language understanding and, therefore, widely demanded by numerous Natural Language Processing applications. In particular, left-to-right and top-down transition-based ...