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This paper proposes a method of extracting English multi-word named entities and their Japanese equivalents from a parallel corpus. The aim of our research is to extract multi-word named entities …...

We consider the problem of training logis- tic regression models for binary classifi- cation in information extraction and infor- mation retrieval tasks. Fitting probabilis- tic models for use with such …...

Named Entity Recognition (NER) is a fundamental task in text mining and nat- ural language understanding. Current ap- proaches to NER (mostly based on super- vised learning) perform well on …...

Aligning sentences belonging to compa- rable monolingual corpora has been sug- gested as a first step towards training text rewriting algorithms, for tasks such as summarization or paraphrasing. We present …...

In this paper we present a semantic archi- tecture that was employed for processing two different SemEval 2007 tasks: Task 4 (Classification of Semantic Relations be- tween Nominals) and Task …...

String transformation, which maps a source string s into its desirable form t∗, is related to various applications including stemming, lemmatization, and spelling correction. The essential and important step for …...

In this paper, we propose a novel way to include unsupervised feature selection meth- ods in probabilistic taxonomy learning mod- els. We leverage on the computation of logistic regression to …...

We address the challenge of automatically generating questions from reading materials for educational practice and assessment. Our approach is to overgenerate questions, then rank them. We use manually written rules …...

We show how features can easily be added to standard generative models for unsuper- vised learning, without requiring complex new training methods. In particular, each component multinomial of a generative …...

We describe tree edit models for representing sequences of tree transformations involving complex reordering phenomena and demon- strate that they offer a simple, intuitive, and effective method for modeling pairs …...

Online user comments contain valuable user opinions. Comments vary greatly in quality and detecting high quality comments is a subtask of opinion mining and summarization research. Finding attentive comments that …...

Our study focuses on opinion mining of several medi- cal forums dedicated to Hearing Loss (HL). Surgeries related to HL are the most common surgeries in North America; thus, they …...

This paper describes a set of experi- ments on two sub-tasks of Quality Esti- mation of Machine Translation (MT) out- put. Sentence-level ranking of alternative MT outputs is done with …...

A discourse typically involves numerous en- tities, but few are mentioned more than once. Distinguishing discourse entities that die out after just one mention (singletons) from those that lead longer …...

The results obtained by the BUAP team at Task 1 of SemEval 2014 are presented in this paper. The run submitted is a supervised ver- sion based on two classification …...

Text-based document geolocation is com- monly rooted in language-based infor- mation retrieval techniques over geodesic grids. These methods ignore the natural hierarchy of cells in such grids and fall afoul …...

This paper presents the system submitted by KUNLPLab for SemEval-2014 Task9 - Subtask B: Message Polarity on Twitter data. Lexicon features and bag-of-words features are mainly used to represent the …...

This paper describes the details of our system submitted to the SemEval-2014 shared task about aspect-based sentiment analysis on review texts. We participated in subtask 2 (prediction of the polarity …...

We present a simple preordering approach for machine translation based on a feature- rich logistic regression model to predict whether two children of the same node in the source-side parse …...

We present a simple and yet effective ap- proach that can incorporate rationales elicited from annotators into the training of any off- the-shelf classifier. We show that our sim- ple …...

We propose the use of neural networks to model source-side preordering for faster and better statistical machine translation. The neu- ral network trains a logistic regression model to predict whether …...

Monolingual alignment is the task of pair- ing semantically similar units from two pieces of text. We report a top-performing supervised aligner that operates on short text snippets. We employ …...

This paper describes our contribution in Opin- ion Target Extraction OTE and Sentiment Po- larity sub tasks of SemEval 2015 ABSA task. A CRF model with IOB notation has been …...

This paper describes our sentiment analysis systems which have been built for SemEval- 2015 Task 10 Subtask B and E. For sub- task B, a Logistic Regression classifier has been …...

This paper describes MITRE’s participation in the Paraphrase and Semantic Similar- ity in Twitter task (SemEval-2015 Task 1). This effort placed first in Semantic Similar- ity and second in Paraphrase …...

This paper describes SWATAC, a system built for SemEval-2015’s Task 10 Subtask B, namely the Message Polarity Classification Task. Given a tweet, the system classifies the sentiment as either positive, …...

This paper describes system details and results of team “EOF” from the Univer- sity of Melbourne in the shared task of ALTA 2016, which addresses the use of cross document …...

Extraction and interpretation of temporal information from clinical text is essential for clinical practitioners and researchers. SemEval 2016 Task 12 (Clinical TempEval) addressed this challenge using the THYME1 corpus, a …...

This paper describes our system submitted for the Sentiment Analysis in Twitter task of SemEval-2016, and specifically for the Mes- sage Polarity Classification subtask. We used a system that combines …...

AbstractThis study proposes a computational model of the discourse segments in lyrics to understand and to model the structure of lyrics. To test our hypothesis that discourse segmentations in lyrics …...

AbstractIn this paper, we introduce the task of targeted aspect-based sentiment analysis. The goal is to extract fine-grained information with respect to entities mentioned in user comments. This work extends …...

This paper describes our sentiment analysis system which has been built for Sentiment Analysis in Twitter Task of SemEval-2016. We have used a Logistic Regression classifier with different groups of …...

This paper describes our contribution in Opin- ion Target Extraction and Sentiment Polarity sub-tasks of SemEval 2016 ABSA task. Conditional Random Field model has beenA adopted for opinion target extraction. …...

AbstractThis paper presents some experiments for specialising Paragraph Vectors, a new technique for creating text fragment (phrase, sentence, paragraph, text, ...) embedding vectors, for text polarity detection. The first extension …...

We present the Stanford Question Answer- ing Dataset (SQuAD), a new reading compre- hension dataset consisting of 100,000+ ques- tions posed by crowdworkers on a set of Wikipedia articles, where …...

AbstractThis paper describes the Amobee sentiment analysis system, adapted to compete in SemEval 2017 task 4. The system consists of two parts: a supervised training of RNN models based on …...

AbstractThe freedom of the Deep Web offers a safe place where people can express themselves anonymously but they also can conduct illegal activities. In this paper, we present and make …...

AbstractExperimenting with a new dataset of 1.6M user comments from a news portal and an existing dataset of 115K Wikipedia talk page comments, we show that an RNN operating on …...

AbstractWe propose a new, socially-impactful task for natural language processing: from a news corpus, extract names of persons who have been killed by police. We present a newly collected police …...

AbstractThis paper reports team IITPB’s participation in the SemEval 2017 Task 5 on ‘Fine-grained sentiment analysis on financial microblogs and news’. We developed 2 systems for the two tracks. One …...

AbstractThe paper describes the participation of the team “TwiSE” in the SemEval-2017 challenge. Specifically, I participated at Task 4 entitled “Sentiment Analysis in Twitter” for which I implemented systems for …...

AbstractWe introduce Zipporah, a fast and scalable data cleaning system. We propose a novel type of bag-of-words translation feature, and train logistic regression models to classify good data and synthetic …...

AbstractIn this paper, we describe a methodology to predict emoji in tweets. Our approach is based on the classic bag-of-words model in conjunction with word embeddings. The used classification algorithm …...

The Part-Of-Speech tag of a word can pro- vide crucial information for a large num- ber of tasks, and so, it is of utmost im- portance that the POS tagged …...

The current study investigates approaches to automatic metaphor identification, the compu- tational task of identifying whether a word or phrase in a portion of text is an instance of metaphor. …...

AbstractIn this paper, we present the results obtained using bi-directional long short-term memory (BiLSTM) with and without attention and Logistic Regression (LR) models for SemEval-2019 Task 5 titled ”HatEval: Multilingual …...

AbstractThis paper describes the participation of DBMS-KU team in the SemEval 2019 Task 9, that is, suggestion mining from online reviews and forums. To deal with this task, we explore …...

AbstractThis paper describes the Pioquinto Manterola Hyperpartisan News Detector, which participated in SemEval-2019 Task 4. Hyperpartisan news is highly polarized and takes a very biased or one–sided view of a …...

AbstractWe explore the challenge of action prediction from textual descriptions of scenes, a testbed to approximate whether text inference can be used to predict upcoming actions. As a case of …...

AbstractIncivility in public discourse has been a major concern in recent times as it can affect the quality and tenacity of the discourse negatively. In this paper, we present neural …...

AbstractIn this article, we present a novel multi-domain dataset of Polish text reviews, annotated with sentiment on different levels: sentences and the whole documents. The annotation was made by linguists …...

AbstractWe describe our submission to SemEval-2019 Task 4 on Hyperpartisan News Detection. We rely on a variety of engineered features originally used to detect propaganda. This is based on the …...

In this paper, we conducted an aspect-based sentiment analysis using Google Maps user reviews of Indonesia’s tourism destinations which are Borobudur and Prambanan Temple. The aspects we used are Attractions, …...

AbstractIn recent years, fake news detection has been an emerging research area. In this paper, we put forward a novel statistical approach for the generation of feature vectors to describe …...

AbstractThis paper describes the Duluth systems that participated in SemEval–2020 Task 12, Multilingual Offensive Language Identification in Social Media (OffensEval–2020). We participated in the three English language tasks. Our systems …...

AbstractThe motivation behind this work lies in the need to differentiate between similar signs that differ in non-manual components present in any sign. To this end, we recorded full sentences …...

AbstractIn this paper we describe our contribution to the Semeval-2020 Humor Assessment task. We essentially use three different features that are passed into a ridge regression to determine a funniness …...

This paper aims to investigate the variation between two Chinese causative auxiliaries shi ‘使’ and rang ‘讓’ from a corpus-based perspective. We conduct a logistic regression analysis to the Chinese …...

AbstractThe paper describes the systems submitted to SemEval-2020 Task 8: Memotion by the ‘NIT-Agartala-NLP-Team’. A dataset of 8879 memes was made available by the task organizers to train and test …...

AbstractThis paper describes the BERT-based models proposed for two subtasks in SemEval-2020 Task 11: Detection of Propaganda Techniques in News Articles. We first build the model for Span Identification (SI) …...

AbstractThe article describes a fast solution to propaganda detection at SemEval-2020 Task 11, based on feature adjustment. We use per-token vectorization of features and a simple Logistic Regression classifier to …...

AbstractWritten communication is of utmost importance to the progress of scientific research. The speed of such development, however, may be affected by the scarcity of reviewers to referee the quality …...

AbstractThis paper presents our system submission to task 5: Toxic Spans Detection of the SemEval-2021 competition. The competition aims at detecting the spans that make a toxic span toxic. In …...

AbstractThis paper describes team LCP-RIT’s submission to the SemEval-2021 Task 1: Lexical Complexity Prediction (LCP). The task organizers provided participants with an augmented version of CompLex (Shardlow et al., 2020), …...

AbstractWe adopt an evolutionary view on language change in which cognitive factors (in addition to social ones) affect the fitness of words and their success in the linguistic ecosystem. Specifically, …...

AbstractThis paper describes the submission of the team Amrita_CEN to the shared task on iSarcasm Eval: Intended Sarcasm Detection in English and Arabic at SemEval 2022. We employed machine learning …...

AbstractAutomatic identification of cyberbullying from textual content is known to be a challenging task. The challenges arise from the inherent structure of cyberbullying and the lack of labeled large-scale corpus, …...

AbstractIn this paper, we formulate system combination for grammatical error correction (GEC) as a simple machine learning task: binary classification. We demonstrate that with the right problem formulation, a simple …...

AbstractThis work deploys linguistically motivated features to classify paragraph-level text into fiction and non-fiction genre using a logistic regression model and infers lexical and syntactic properties that distinguish the two …...

AbstractThe needs for mediation are increasing rapidly along with the increasing number of cases of the alimony for the elderly in recent years. Offering a prediction mechanism for predicting the …...

AbstractThis paper presents, to the best of our knowledge, the first ever publicly available annotated dataset for sentiment classification and semantic polarity dictionary for Georgian. The characteristics of these resources …...

AbstractDetecting MEME images to be misogynous or not is an application useful on curbing online hateful information against women. In the SemEval-2022 Multimedia Automatic Misogyny Identification (MAMI) challenge, we designed …...

AbstractThis paper describes our participation as team FramingFreaks in the SemEval-2023 task 3 “Category and Framing Predictions in online news in a multi-lingual setup.” We participated in subtasks 1 and …...

AbstractLiterature permeates through almost every facet of our lives, whether through books, magazines, or internet articles. Moreover, every piece of written work contains ideas and opinions that we tend to …...

AbstractThis paper presents our work on the SemEval-2023 Task 10 Explainable Detection of Online Sexism (EDOS) using lexicon-based models. Our approach consists of three main steps: lexicon construction based on …...

AbstractThe rapid growth of online communication using social media platforms has led to an increase in the presence of hate speech, especially in terms of sexist language online. The proliferation …...