Лексикалық ерекшеліктер

A new almost-parsing language model incorporat- ing multiple knowledge sources that is based upon the concept of Constraint Dependency Grammars is presented in this paper. Lexical features and syn- tactic …...

The success of supervised learning approaches to word sense disambiguation is largely de- pendent on the features used to represent the context in which an ambiguous word occurs. Previous work …...

This paper reports the results of experiments using memory-based learning to guide a de- terministic dependency parser for unrestricted natural language text. Using data from a small treebank of Swedish, …...

Lexical features are key to many ap- proaches to sentiment analysis and opin- ion detection. A variety of representations have been used, including single words, multi-word Ngrams, phrases, and lexico- …...

We present a method for Noun Phrase chunking in Hebrew. We show that the traditional definition of base-NPs as non- recursive noun phrases does not apply in Hebrew, and propose …...

AbstractIn this article we address the task of automatic text structuring into linear and non-overlapping thematic episodes. Our investigation reports on the use of various lexical, acoustic and syntactic features, …...

We study the issue of porting a known NLP method to a language with little existing NLP resources, specifically Hebrew SVM-based chunking. We introduce two SVM-based methods – Model Tampering …...

This study addresses the problem of au- tomatically detecting decisions in conver- sational speech. We formulate the prob- lem as classifying decision-making units at two levels of granularity: dialogue acts …...

Many acoustic approaches to prosodic la- beling in English have employed only lo- cal classifiers, although text-based classifi- cation has employed some sequential mod- els. In this paper we employ …...

We present the first results on parsing the SYNTAGRUS treebank of Russian with a data-driven dependency parser, achieving a labeled attachment score of over 82% and an unlabeled attachment score …...

. The Phrase-Based Statistical Machine Translation (PB-SMT) model has recently begun to include source context modeling, under the assumption that the proper lexical choice of an ambiguous word can be …...

Automatically detecting human social in- tentions from spoken conversation is an important task for dialogue understand- ing. Since the social intentions of the speaker may differ from what is perceived …...

Question detection serves great purposes in the cQA question retrieval task. While detecting questions in standard language data corpus is relatively easy, it becomes a great challenge for online content. …...

During face-to-face conversation, people naturally integrate speech, gestures and higher level language interpretations to predict the right time to start talking or to give backchannel feedback. In this paper we …...

This paper presents a two-stage approach to summarizing multiple contrastive viewpoints in opinionated text. In the first stage, we use an unsupervised probabilistic approach to model and extract multiple viewpoints …...

Attempts to profile authors according to their characteristics extracted from textual data, in- cluding native language, have drawn attention in recent years, via various machine learn- ing approaches utilising mostly …...

Traditional approaches to sentiment classifica- tion rely on lexical features, syntax-based fea- tures or a combination of the two. We pro- pose semantic features using word senses for a supervised …...

We present a system for automatic identification of schizophrenic patients and healthy controls based on narratives the subjects recounted about emotional experiences in their own life. The focus of the …...

Previous approaches to the task of native language identification (Koppel et al., 2005) have been limited to small, within-corpus evaluations. Because these are restrictive and unreliable, we apply cross-corpus evaluation …...

There are many languages considered to be low-density languages, either because the population speaking the language is not very large, or because insufficient digitized text material is available in the …...

This paper describes University of Leipzig’s approach to SemEval-2013 task 2B on Sen- timent Analysis in Twitter: message polar- ity classification. Our system is designed to function as a baseline, …...

In this paper we present the results of exper- iments comparing (a) rich syntactic and se- mantic feature sets and (b) big context win- dows, for the TempEval time expression …...

CLaC-CORE, an exhaustive feature combina- tion system ranked 4th among 34 teams in the Semantic Textual Similarity shared task STS 2013. Using a core set of 11 lexical features of …...

Wizard-of-Oz experimental setup in a dia- logue system is commonly used to gather data for informing an automated version of that system. Previous work has exposed depen- dencies between user …...

This paper is an overview of the SwatCS system submitted to SemEval-2013 Task 2A: Contextual Polarity Disambiguation. The sen- timent of individual phrases within a tweet are labeled using a …...

The informal nature of social media text renders it very difficult to be automati- cally processed by natural language pro- cessing tools. Text normalization, which corresponds to restoring the non-standard …...

This paper describes the systems deployed by the ALPAGE team to participate to the SemEval-2014 Task on Broad-Coverage Semantic Dependency Parsing. We de- veloped two transition-based dependency parsers with extended …...

Definiteness expresses a constellation of semantic, pragmatic, and discourse properties—the communicative functions—of an NP. We present a supervised classifier for English NPs that uses lexical, morphological, and syntactic features to …...

We describe our approach for the SemEval-2014 task 9: Sentiment Analy- sis in Twitter. We make use of an en- semble learning method for sentiment classification of tweets that relies …...

In this paper we present the evaluation of different features for multiligual and cross- level semantic textual similarity. Three dif- ferent types of features were used: lexical, knowledge-based and corpus-based. …...

In this paper, we describe our system for the Sentiment Analysis of Twitter shared task in SemEval 2014. Our system uses an SVM classifier along with rich set of lexical …...

AbstractThis paper presents a novel task of cross-language authorship attribution (CLAA), an extension of authorship attribution task to multilingual settings: given data labelled with authors in language X, the objective …...

In the context of Social Media Analytics, Natural Language Processing tools face new chal- lenges on on-line conversational text, such as microblogs, chat, or text messages, because of the specificity …...

This paper describes the participation of the HITSZ-ICRC team on the Answer Selection Challenge in SemEval-2015. Our team parti- cipated in English subtask A, English subtask B and Arabic task. …...

A simile is a comparison between two essentially unlike things, such as “Jane swims like a dolphin”. Similes often ex- press a positive or negative sentiment to- ward something, but …...

In this paper we investigate how readabil- ity varies between texts originally writ- ten in English and texts translated into English. For quantification, we analyze several factors that are relevant …...

AbstractAutomated short-answer grading is key to help close the automation loop for large-scale, computerised testing in education. A wide range of features on different levels of linguistic processing has been …...

SemEval 2016 Task 12 addresses temporal reasoning in the clinical domain. In this paper, we present our participation for relation ex- traction based on gold standard entities (sub- tasks DR …...

AbstractIn this paper, we first build a manually annotated named entity corpus of Mongolian. Then, we propose three morphological processing methods and study comprehensive features, including syllable features, lexical features, …...

The problem of accurately predicting rela- tive reading difficulty across a set of sen- tences arises in a number of important natu- ral language applications, such as finding and curating …...

AbstractWe extend classic review mining work by building a binary classifier that predicts whether a review of a documentary film was written by an expert or a layman with 90.70% …...

AbstractWhile measuring the readability of texts has been a long-standing research topic, assessing the technicality of terms has only been addressed more recently and mostly for the English language. In …...

AbstractWe consider the task of predicting how literary a text is, with a gold standard from human ratings. Aside from a standard bigram baseline, we apply rich syntactic tree fragments, …...

This paper aims to present a lexical-based approach in order to identify deception in Indonesian transcribed interviews. Using word calculation from the psychological point of view, we classify each subject …...

AbstractThis paper describes our system participation in the SemEval-2017 Task 8 ‘RumourEval: Determining rumour veracity and support for rumours’. The objective of this task was to predict the stance and …...

Emotions are found to be frequently involved in the exclamative sentences. This paper aims to examine the interaction between exclama- tive sentences and emotions in Chinese social media. We propose …...

AbstractThis paper describes the system used and results obtained for team FOI DSS at SemEval-2018 Task 1: Affect In Tweets. The team participated in all English language subtasks, with a …...

AbstractWe propose a novel tensor embedding method that can effectively extract lexical features for humor recognition. Specifically, we use word-word co-occurrence to encode the contextual content of documents, and then …...

AbstractThe advent of micro-blogging sites has paved the way for researchers to collect and analyze huge volumes of data in recent years. Twitter, being one of the leading social networking …...

AbstractOpen-domain Keyphrase extraction (KPE) on the Web is a fundamental yet complex NLP task with a wide range of practical applications within the field of Information Retrieval. In contrast to …...

AbstractFew-shot crosslingual transfer has been shown to outperform its zero-shot counterpart with pretrained encoders like multilingual BERT. Despite its growing popularity, little to no attention has been paid to standardizing …...

AbstractThis paper revisits feature engineering approaches for predicting the complexity level of English words in a particular context using regression techniques. Our best submission to the Lexical Complexity Prediction (LCP) …...

AbstractWe present two convolutional neural networks for predicting the complexity of words and phrases in context on a continuous scale. Both models utilize word and character embeddings alongside lexical features …...

AbstractBeing able to reliably estimate self-disclosure – a key component of friendship and intimacy – from language is important for many psychology studies. We build single-task models on five self-disclosure …...

AbstractConflict prediction in communication is integral to the design of virtual agents that support successful teamwork by providing timely assistance. The aim of our research is to analyze discourse to …...

AbstractIn-context learning (ICL) is an important paradigm for adapting large language models (LLMs) to new tasks, but the generalization behavior of ICL remains poorly understood. We investigate the inductive biases …...