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Negation and Speculation in NLP: A Survey, Corpora, Methods, and Applications
2022
Applied Sciences
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Furthermore, we discuss the ongoing research into recent rule-based, supervised, and transfer learning techniques for the detection of negating and speculative content. ...
Adding more syntactic features may alleviate the limitations of the existing techniques, such as cue ambiguity and detecting the discontinuous scopes. ...
McKenna and Steedman proposed the Structural Tree Recursive Neural Network (STRNN) to detect the negation scope on the SEM 2012* test corpus [97] . ...
doi:10.3390/app12105209
fatcat:jzm5hjhcqbbr5ck6cosat7n5zq
Recent advances in processing negation
2020
Natural Language Engineering
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We continue the survey with a description of automated approaches to process negation, ranging from early rule-based systems to systems built with traditional machine learning and neural networks. ...
We also provide information about corpora containing negation annotations in English and other languages, which usually include a combination of annotations of negation cues, scopes, foci, and negated ...
Focus of negation identification Automated systems to predict the focus of negation as annotated in PB-FOC are built using traditional machine learning algorithms as well as sophisticated neural networks ...
doi:10.1017/s1351324920000534
fatcat:lq76xxt6ofg2hk3j4oqimqzbx4
Improving Sentiment Analysis with Multi-task Learning of Negation
[article]
2019
arXiv
pre-print
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Sentiment analysis is directly affected by compositional phenomena in language that act on the prior polarity of the words and phrases found in the text. ...
Negation is the most prevalent of these phenomena and in order to correctly predict sentiment, a classifier must be able to identify negation and disentangle the effect that its scope has on the final ...
Interest in the task was further spurred by the *SEM shared task (Morante and Blanco, 2012) , which focused on detection of negation cues and scopes, in addition to detection of negated events and their ...
arXiv:1906.07610v2
fatcat:ctkc2vfnrbachj4booa4ddjokm
Using Structured Representation and Data: A Hybrid Model for Negation and Sentiment in Customer Service Conversations
2019
Proceedings of the Tenth Workshop on Computational Approaches to Subjectivity, Sentiment and Social Media Analysis
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We further investigate the results of negation scope detection for the sentiment prediction task on customer service conversation data using both a traditional SVM and a Neural Network. ...
Using semantic knowledge and syntactic structure from constituency parse trees, we propose an algorithm for scope detection that performs comparable to state of the art BiLSTM. ...
Majority of the previous work in scope detection has been dominated by SVMs or Neural Networks, which require expensive annotated training data. ...
doi:10.18653/v1/w19-1306
dblp:conf/wassa/MisraBMT19
fatcat:jt3wzblbnzadtnpktsgdux235e
Extracting semantically enriched events from biomedical literature
2012
BMC Bioinformatics
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EventMine-MK has been evaluated on the BioNLP'09 Shared Task subtask of detecting negated and speculated events. ...
Research into event-based text mining from the biomedical literature has been growing in popularity to facilitate the development of advanced biomedical text mining systems. ...
Acknowledgements This work was supported by the Biotechnology and Biological Sciences Research Council (BBSRC) [grant number BB/G013160/1] jointly with AstraZeneca and by the Joint Information Systems ...
doi:10.1186/1471-2105-13-108
pmid:22621266
pmcid:PMC3464657
fatcat:fpxrrl7ukjekbjjpgqwtg6ocbe
Negation in Norwegian: an annotated dataset
2021
Nordic Conference of Computational Linguistics
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Negation cues and their in-sentence scopes have been annotated across more than 11K sentences spanning more than 400 documents for a subset of the Norwegian Review Corpus (NoReC). ...
This paper introduces NoReC neg -the first annotated dataset of negation for Norwegian. ...
Acknowledgements This work has been carried out as part of the SANT project (Sentiment Analysis for Norwegian Text), funded by the Research Council of Norway (grant number 270908). ...
dblp:conf/nodalida/MaehlumBKOV21
fatcat:ml2gu4g7wnahdgryzd6vg35fhe
Multi-task Learning of Negation and Speculation for Targeted Sentiment Classification
[article]
2021
arXiv
pre-print
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In this paper, we propose a multi-task learning method to incorporate information from syntactic and semantic auxiliary tasks, including negation and speculation scope detection, to create English-language ...
The majority of work in targeted sentiment analysis has concentrated on finding better methods to improve the overall results. ...
Acknowledgements This work has been carried out as part of the SANT project (Sentiment Analysis for Norwegian Text), funded by the Research Council of Norway (grant ...
arXiv:2010.08318v2
fatcat:z7b3fmynobarzmj344hadthupu
A Survey on Event Extraction for Natural Language Understanding: Riding the Biomedical Literature Wave
2021
IEEE Access
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To cope with the everincreasing number of publications, researchers are experiencing a surge of interest in extracting valuable, structured, concise, and unambiguous information from plain texts. ...
Third, we deeply explore the most representative methods and present an analysis of the current state-of-the-art, accompanied by performance discussion. ...
G.F. conducted the review and wrote the manuscript. G.M. and A.C. supervised all steps of the work and revised each section. ...
doi:10.1109/access.2021.3130956
fatcat:wlr7zeikdva77ojuppqx3vmocy
Unsupervised inference of implicit biomedical events using context triggers
2020
BMC Bioinformatics
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Event extraction from the biomedical literature is one of the most actively researched areas in biomedical text mining and natural language processing. ...
Moreover, it also helps to boost the performance of existing systems by allowing them to detect additional cross-sentence events. ...
J-WC wrote the first draft of the manuscript with support from JP. JP supervised all steps of the research. ...
doi:10.1186/s12859-020-3341-0
pmid:31992184
pmcid:PMC6988352
fatcat:edrrrkh7xzdafexzynpyuo7hq4
Evaluative Language Beyond Bags of Words: Linguistic Insights and Computational Applications
2017
Computational Linguistics
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We end the review by outlining what we believe the future directions of sentiment analysis are, and the role that discourse and contextual information need to play. * ...
In this survey, we show how incorporating linguistic insights, discourse information, and other contextual phenomena, in combination with the statistical exploitation of data, can result in an improvement ...
Acknowledgments This research was funded by a Discovery Grant from the Natural Sciences and Engineering Council of Canada to Maite Taboada, and ERC grant 269427 (STAC). ...
doi:10.1162/coli_a_00278
fatcat:yphpwgzrafhgxbit55rjhyhix4
Unsupervised Event Graph Representation and Similarity Learning on Biomedical Literature
2021
Sensors
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buried in texts. ...
The automatic extraction of biomedical events from the scientific literature has drawn keen interest in the last several years, recognizing complex and semantically rich graphical interactions otherwise ...
Acknowledgments: We thank Eleonora Bertoni for her precious help in preparing the datasets, implementing the baseline, and conducting the experiments. ...
doi:10.3390/s22010003
pmid:35009544
pmcid:PMC8747118
fatcat:zghkmzt3wnf27cvh2p5tcvrvei
On the Explainability of Natural Language Processing Deep Models
2022
ACM Computing Surveys
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Such challenges can be attributed to the lack of input structure in textual data, the use of word embeddings that add to the opacity of the models and the difficulty of the visualization of the inner workings ...
Despite their success, deep networks are used as black-box models with outputs that are not easily explainable during the learning and the prediction phases. ...
A subset of the interpretability methods is also surveyed in [85] , where a comprehensive study is presented covering activation maximization, network inversion, deconvolutional neural networks, and network ...
doi:10.1145/3529755
fatcat:hsgre77t2vhxbciswxrcjtncwi
Computational linguistics and grammar engineering
[article]
2021
Zenodo
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We discuss the relevance of HPSG for computational linguistics, and the relevance of computational linguistics for HPSG, including: the theoretical and computational infrastructure required to carry out ...
computational studies with HPSG; computational resources developed within HPSG; how those resources are deployed, for both practical applications and linguistic research; and finally, a sampling of linguistic ...
Acknowledgments We would like to thank Stephan Oepen for helpful comments on an early draft of this chapter, Stefan Müller for detailed comments as volume editor and Elizabeth Pankratz for careful copy ...
doi:10.5281/zenodo.5599867
fatcat:qfrfqb5fnngdtbbqhhm3dkmmua
(DIS)ABLING BODY AND CONSCIOUSNESS: TECHNOLOGICAL AFTERNESS AND AFTER-HUMANS IN REALIVE AND UPGRADE
2019
Trabalhos em Lingüística Aplicada
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Upgrade (2018) shows us the metamorphosis of Grey Trace, a luddite, by an installed biomechanical enhancer chip, Stem. ...
In the film Realive (2016) we encounter an extension of the self beyond death by re-placing it into another body. ...
Creation of beings (and by using "beings", I am broadening the scope for inclusion of human, non-human animals, insects, bacteria, machines and other cybernetic systems etc.) has always been an act of ...
doi:10.1590/010318135360515822019
fatcat:n5vysqi3q5ge7mblpkm7qgcicq
Multitask Learning of Negation and Speculation using Transformers
2020
Proceedings of the 11th International Workshop on Health Text Mining and Information Analysis
unpublished
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Prior work has individually addressed Negation Detection and Speculation Detection, and both have been addressed in the same way, using a 2 stage pipelined approach: Cue Detection followed by Scope Resolution ...
Detecting negation and speculation in language has been a task of considerable interest to the biomedical community, as it is a key component of Information Extraction systems from Biomedical documents ...
Fei et al. (2020) used a Recursive Neural Network (RecurNN) followed by a CRF to detect the scope in a sentence which is named as the Recur-CRF model. ...
doi:10.18653/v1/2020.louhi-1.9
fatcat:zuj3djly45dhhefuim7una25re
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