Results 1 to 10 of about 14,560 (254)
SemEval-2016 Task 5: Aspect Based Sentiment Analysis [PDF]
International audienceThis paper describes the SemEval 2016 shared task on Aspect Based Sentiment Analysis (ABSA), a continuation of the respective tasks of 2014 and 2015.
S Senthilvelan+2 more
exaly +11 more sources
SemEval-2016 Task 6: Detecting Stance in Tweets [PDF]
10th International Workshop on Semantic Evaluation (SemEval-2016), 16-17 June 2016, San Diego, California ...
Parinaz Sobhani
exaly +5 more sources
SemEval-2023 Task 12: Sentiment Analysis for African Languages (AfriSenti-SemEval) [PDF]
We present the first Africentric SemEval Shared task, Sentiment Analysis for African Languages (AfriSenti-SemEval) - The dataset is available at https://github.com/afrisenti-semeval/afrisent-semeval-2023. AfriSenti-SemEval is a sentiment classification challenge in 14 African languages: Amharic, Algerian Arabic, Hausa, Igbo, Kinyarwanda, Moroccan ...
Shamsuddeen Hassan Muhammad+9 more
arxiv +5 more sources
Luminoso at SemEval-2018 Task 10: Distinguishing Attributes Using Text Corpora and Relational Knowledge [PDF]
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. In this paper, we describe how we trained a linear classifier on a small number of semantically-informed features to achieve an $F_1$ score of 0.7368 on the task, close to the ...
Lowry-Duda, Joanna, Speer, Robyn
arxiv +3 more sources
In this paper, we describe the SemEval-2010 shared task on "Linking Events and Their Participants in Discourse". This task is a variant of the classical semantic role labelling task. The novel aspect is that we focus on linking local semantic argument structures across sentence boundaries.
Josef Ruppenhofer+4 more
openalex +5 more sources
SemEval-2014 Task 9: Sentiment Analysis in Twitter [PDF]
Sentiment analysis, microblog sentiment analysis, Twitter opinion mining, sarcasm, LiveJournal ...
Sara Rosenthal+3 more
openalex +4 more sources
Duluth at SemEval-2017 Task 6: Language Models in Humor Detection [PDF]
This paper describes the Duluth system that participated in SemEval-2017 Task 6 #HashtagWars: Learning a Sense of Humor. The system participated in Subtasks A and B using N-gram language models, ranking highly in the task evaluation. This paper discusses the results of our system in the development and evaluation stages and from two post-evaluation ...
Pedersen, Ted, Yan, Xinru
arxiv +3 more sources
SemEval-2015 Task 6: Clinical TempEval [PDF]
Clinical TempEval 2015 brought the temporal information extraction tasks of past TempEval campaigns to the clinical domain. Nine sub-tasks were included, covering problems in time expression identification, event expression identification and temporal relation identification.
Steven Bethard+4 more
openalex +3 more sources
What is SemEval evaluating? A Systematic Analysis of Evaluation Campaigns in NLP [PDF]
SemEval is the primary venue in the NLP community for the proposal of new challenges and for the systematic empirical evaluation of NLP systems. This paper provides a systematic quantitative analysis of SemEval aiming to evidence the patterns of the contributions behind SemEval.
Oskar Wysocki+3 more
arxiv +5 more sources
SemEval-2016 Task 12: Clinical TempEval [PDF]
Clinical TempEval 2016 evaluated temporal information extraction systems on the clinical domain. Nine sub-tasks were included, covering problems in time expression identification, event expression identification and temporal relation identification. Participant systems were trained and evaluated on a corpus of clinical and pathology notes from the Mayo
Steven Bethard+5 more
openalex +3 more sources