Results 81 to 90 of about 21,648 (265)

SemEval-2007 task 07 [PDF]

Proceedings of the 4th International Workshop on Semantic Evaluations - SemEval '07, 2007
This paper presents the coarse-grained English all-words task at SemEval-2007. We describe our experience in producing a coarse version of the WordNet sense inventory and preparing the sense-tagged corpus for the task. We present the results of participating systems and discuss future directions.
NAVIGLI, ROBERTO, K. LITKOWSKI, O. HARGRAVES   +2 more
openaire   +2 more sources

Word Sense Disambiguation Based on RegNet With Efficient Channel Attention and Dilated Convolution

IEEE Access, 2023
Word sense disambiguation (WSD) is one of key problems in field of natural language processing. Ambiguous word often has different meanings in different contexts.
Chun-Xiang Zhang, Ya-Li Shao, Xue-Yao Gao   +2 more
doaj   +1 more source

SemEval-2021 Task 5: Toxic Spans Detection

International Workshop on Semantic Evaluation, 2021
The Toxic Spans Detection task of SemEval-2021 required participants to predict the spans of toxic posts that were responsible for the toxic label of the posts.
John Pavlopoulos, Jeffrey Scott Sorensen, Leo Laugier, I. Androutsopoulos   +3 more
semanticscholar   +1 more source

A Single Attention-Based Combination of CNN and RNN for Relation Classification

IEEE Access, 2019
As a vital task in natural language processing, relation classification aims to identify relation types between entities from texts. In this paper, we propose a novel Att-RCNN model to extract text features and classify relations by combining recurrent ...
Xiaoyu Guo, Hui Zhang, Haijun Yang, Lianyuan Xu, Zhiwen Ye   +4 more
doaj   +1 more source

Luminoso at SemEval-2018 Task 10: Distinguishing Attributes Using Text Corpora and Relational Knowledge

, 2018
Luminoso participated in the SemEval 2018 task on "Capturing Discriminative Attributes" with a system based on ConceptNet, an open knowledge graph focused on general knowledge.
Lowry-Duda, Joanna, Speer, Robyn
core   +1 more source

Tweet2Vec: Learning Tweet Embeddings Using Character-level CNN-LSTM Encoder-Decoder [PDF]

, 2016
We present Tweet2Vec, a novel method for generating general-purpose vector representation of tweets. The model learns tweet embeddings using character-level CNN-LSTM encoder-decoder.
Kiros R., Mikolov T., Sutskever I., Vosoughi S.   +3 more
core   +2 more sources

SemEval-2014 Task 4: Aspect Based Sentiment Analysis

International Workshop on Semantic Evaluation, 2014
Sentiment analysis is increasingly viewed as a vital task both from an academic and a commercial standpoint. The majority of current approaches, however, attempt to detect the overall polarity of a sentence, paragraph, or text span, irrespective of the ...
Maria Pontiki, Dimitris Galanis, John Pavlopoulos, Haris Papageorgiou, Ion Androutsopoulos, S. Manandhar   +5 more
semanticscholar   +1 more source

SemEval-2020 Task 9: Overview of Sentiment Analysis of Code-Mixed Tweets [PDF]

International Workshop on Semantic Evaluation, 2020
In this paper, we present the results of the SemEval-2020 Task 9 on Sentiment Analysis of Code-Mixed Tweets (SentiMix 2020). We also release and describe our Hinglish (Hindi-English)and Spanglish (Spanish-English) corpora annotated with word-level ...
Parth Patwa, Gustavo Aguilar, Sudipta Kar, S. Pandey, Srinivas Pykl, Björn Gambäck, Tanmoy Chakraborty, T. Solorio, A. Das   +8 more
semanticscholar   +1 more source

Target-Aspect-Sentiment Joint Detection: Uncovering Explicit and Implicit Targets Through Aspect-Target-Context-Aware Detection

IEEE Access
Target Aspect Sentiment Detection (TASD) is challenging because it involves various Natural Language Processing (NLP) subtasks including opinion target detection and sentiment polarity classification.
Mohammad Radi, Nazlia Omar, Wandeep Kaur
doaj   +1 more source

Improving the state-of-the-art in Thai semantic similarity using distributional semantics and ontological information.

PLoS ONE, 2021
Research into semantic similarity has a long history in lexical semantics, and it has applications in many natural language processing (NLP) tasks like word sense disambiguation or machine translation.
Ponrudee Netisopakul, Gerhard Wohlgenannt, Aleksei Pulich, Zar Zar Hlaing   +3 more
doaj   +1 more source