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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 ...
Tratamiento sintáctico de la negación en análisis del sentimiento monolingüe y multilingüe
(2017-09-19)
[Abstract] Dealing with negation in a proper way is a relevant factor in order to obtain high performance sentiment analysis systems. In this framework, we present a method for the treatment of negation in Spanish that ...
Sequence Tagging for Fast Dependency Parsing
(2019)
[Abstract]
Dependency parsing has been built upon the idea of using parsing methods based on shift-reduce or graph-based algorithms in order to identify binary dependency relations between the words in a sentence. In this ...
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, ...
How important is syntactic parsing accuracy? An empirical evaluation on rule-based sentiment analysis
(Springer, 2019)
[Abstract]: Syntactic parsing, the process of obtaining the internal structure of sentences in natural languages, is a crucial task for artificial intelligence applications that need to extract meaning from natural language ...
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) ...
Constituent Parsing as Sequence Labeling
(Association for Computational Linguistics (ACL), 2018)
[Absctract]: We introduce a method to reduce constituent parsing to sequence labeling. For each word wt, it generates a label that encodes: (1) the number of ancestors in the tree that the words wt and wt+1 have in common, ...