ListarOpenAIRE por tema "Natural language processing"
Mostrando ítems 1-13 de 13
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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) ... -
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 ... -
Discontinuous grammar as a foreign language
(Elsevier, 2023-03)[Abstract] In order to achieve deep natural language understanding, syntactic constituent parsing is a vital step, highly demanded by many artificial intelligence systems to process both text and speech. One of the most ... -
Faster shift-reduce constituent parsing with a non-binary, bottom-up strategy
(Elsevier B.V., 2019-10)[Absctract]: An increasingly wide range of artificial intelligence applications rely on syntactic information to process and extract meaning from natural language text or speech, with constituent trees being one of the ... -
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 ... -
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 ... -
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 ... -
On the Use of Parsing for Named Entity Recognition
(MDPI, 2021-01-25)[Abstract] 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 task of identifying the entities ... -
Optimality of syntactic dependency distances
(American Physical Society, 2022-01)[Abstract]: It is often stated that human languages, as other biological systems, are shaped by cost-cutting pressures but, to what extent? Attempts to quantify the degree of optimality of languages by means of an optimality ... -
Parsing as Pretraining
(2020)[Abstract] Recent analyses suggest that encoders pretrained for language modeling capture certain morpho-syntactic structure. However, probing frameworks for word vectors still do not report results on standard setups ... -
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 ... -
Towards Robust Word Embeddings for Noisy Texts
(MDPI, 2020)[Abstract] Research on word embeddings has mainly focused on improving their performance on standard corpora, disregarding the difficulties posed by noisy texts in the form of tweets and other types of non-standard writing ... -
Transition-based semantic role labeling with pointer networks
(Elsevier, 2023-01-25)[Abstract] Semantic role labeling (SRL) focuses on recognizing the predicate–argument structure of a sentence and plays a critical role in many natural language processing tasks such as machine translation and question ...
