Articles

This paper describes our system for SemEval- 2015 Task 13: Multilingual All-Words Sense Disambiguation and Entity Linking. We have participated with our system in the sub-task which aims at monolingual all-words disam- biguation and entity linking. Aside from sys- tem description, we pay closer attention to the evaluation of system …...

We present in this paper our submission to task 13 of SemEval2015, which makes use of background information and external re- sources (DBpedia and Wikipedia) to automat- ically disambiguate texts. Our approach fol- lows two routes for disambiguation: one route is proposed by a state–of–the–art WSD sys- tem, and the …...

We developed a system to participate in shared tasks on the analyzing clinical text. Our system approaches are both machine learning-based and rule-based. We applied the machine learning-based approach for Task 1: disorder identification, and the rule-based approach for Task 2: template slot filling for the disorder. In Task 1, …...

We present a hybrid knowledge-based ap- proach to multilingual word sense disam- biguation using BabelNet. Our approach is based on a hybrid technique derived from the modified version of the Lesk algorithm and the Jiang & Conrath similarity measure. We present our system's runs for the word sense disambiguation subtask …...

Our participation at SemEval’s Multilingual All-Words Sense Disambiguation and Entity Linking task is described. An English entity linking (EL) system is presented, which com- bines the annotations of four public open source EL services. The annotations are com- bined through a weighted voting scheme in- spired on the ROVER method, …...

We introduce an approach to word sense dis- ambiguation and entity linking that combines a set of complementary objectives in an exten- sible multi-objective formalism. During dis- ambiguation the system performs continuous optimization to find optimal probability dis- tributions over candidate senses. Verb senses are disambiguated using a separate neural …...

We implemented a syntactic and semantic tagging system for SemEval 2015 Task 15: Corpus Pattern Analysis. For syntactic tagging, we present a Dependency Chain Search Algorithm that is found to be effective at identifying structurally distant subjects and objects. Other syntactic labels are identified using rules defined over dependency parse …...

This paper describes the first SemEval task to explore the use of Natural Language Process- ing systems for building dictionary entries, in the framework of Corpus Pattern Analysis. CPA is a corpus-driven technique which pro- vides tools and resources to identify and rep- resent unambiguously the main semantic pat- terns …...

This paper describes the system developed by the University of Texas Health Science Center at Houston (UTHealth), for the 2015 SemEval shared task on “Analysis of Clinical Text” (Task 14). We participated in both sub-tasks: Task 1 for “Disorder Identification”, which aims to detect disorder entities and encode them to …...

We describe two tasks—named entity recog- nition (Task 1) and template slot filling (Task 2)—for clinical texts. The tasks leverage an- notations from the ShARe corpus, which con- sists of clinical notes with annotated men- tions disorders, along with their normaliza- tion to a medical terminology and eight addi- tional …...

We present an unsupervised model for induc- ing signed social networks from the content exchanged across network edges. Inference in this model solves three problems simulta- neously: (1) identifying the sign of each edge; (2) characterizing the distribution over content for each edge type; (3) estimating weights for triadic features …...

We present a language agnostic, unsupervised method for inducing morphological transfor- mations between words. The method re- lies on certain regularities manifest in high- dimensional vector spaces. We show that this method is capable of discovering a wide range of morphological rules, which in turn are used to build morphological …...

Vector space word representations are learned from distributional information of words in large corpora. Although such statistics are semantically informative, they disregard the valuable information that is contained in se- mantic lexicons such as WordNet, FrameNet, and the Paraphrase Database. This paper proposes a method for refining vector space representations …...

Previous work has debated whether humans make use of hierarchic syntax when process- ing language (Frank and Bod, 2011; Fos- sum and Levy, 2012). This paper uses an eye-tracking corpus to demonstrate that hier- archic syntax significantly improves reading time prediction over a strong n-gram baseline. This study shows that …...

If speakers use language rationally, they should structure their messages to achieve approximately uniform information density (UID), in order to optimize transmission via a noisy channel. Previous work identified a consistent increase in linguistic information across sentences in text as a signature of the UID hypothesis. This increase was derived …...

Categories such as ANIMAL or FURNITURE are acquired at an early age and play an impor- tant role in processing, organizing, and con- veying world knowledge. Theories of cat- egorization largely agree that categories are characterized by features such as function or appearance and that feature and category acquisition go …...

Most of the current approaches to sentiment analysis of product reviews are dependent on lexical sentiment information and proceed in a bottom-up way, adding new layers of features to lexical data. In this paper, we maintain that a typical product review is not a bag of senti- ments, but a …...

User-generated passwords tend to be memo- rable, but not secure. A random, computer- generated 60-bit string is much more secure. However, users cannot memorize random 60- bit strings. In this paper, we investigate meth- ods for converting arbitrary bit strings into En- glish word sequences (both prose and poetry), and …...

This paper proposes a novel approach to sen- timent analysis that leverages work in soci- ology on symbolic interactionism. The pro- posed approach uses Affect Control Theory (ACT) to analyze readers’ sentiment towards factual (objective) content and towards its en- tities (subject and object). ACT is a theory of affective …...

This paper introduces a task of identifying and semantically classifying lexical expressions in running text. We investigate the online reviews genre, adding semantic supersense annotations to a 55,000 word English corpus that was pre- viously annotated for multiword expressions. The noun and verb supersenses apply to full lexical expressions, whether …...