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This paper presents an empirical evaluation of coreference resolution that covers several interrelated dimensions. The main goal is to complete the comparative analysis from the SemEval-2010 task on Coreference Resolution in Multiple Languages. To do so, the study restricts the number of languages and systems involved, but extends and deepens the analysis of the system outputs, including a more qualitative discussion. The paper compares three automatic coreference resolution systems for three languages (English, Catalan and Spanish) in four evaluation settings, and using four evaluation measures. Given that our main goal is not to provide a comparison between resolution algorithms, these are merely used as tools to shed light on the different conditions under which coreference resolution is evaluated. Although the dimensions are strongly interdependent, making it very difficult to extract general principles, the study reveals a series of interesting issues in relation to coreference resolution: the portability of systems across languages, the influence of the type and quality of input annotations, and the behavior of the scoring measures. [ABSTRACT FROM AUTHOR]

Emotions are inherent to any human activity, including human-computer interactions, and that is the reason why recognizing emotions expressed in natural language is becoming a key feature for the design of more natural user interfaces. In order to obtain useful corpora for this purpose, the manual classification of texts according to their emotional content has been the technique most commonly used by the research community. The use of corpora is widespread in Natural Language Processing, and the existing corpora annotated with emotions support the development, training and evaluation of systems using this type of data. In this paper we present the development of an annotated corpus oriented to the narrative domain, called EmoTales, which uses two different approaches to represent emotional states: emotional categories and emotional dimensions. The corpus consists of a collection of 1,389 English sentences from 18 different folk tales, annotated by 36 different people. Our model of the corpus development process includes a post-processing stage performed after the annotation of the corpus, in which a reference value for each sentence was chosen by taking into account the tags assigned by annotators and some general knowledge about emotions, which is codified in an ontology. The whole process is presented in detail, and revels significant results regarding the corpus such as inter-annotator agreement, while discussing topics such as how human annotators deal with emotional content when performing their work, and presenting some ideas for the application of this corpus that may inspire the research community to develop new ways to annotate corpora using a large set of emotional tags. [ABSTRACT FROM AUTHOR]

Until recently, most systems performing temporal extraction and reasoning from text have focused on recognizing and normalizing temporal expressions alone, for which the TIDES annotation scheme has been adopted. Temporal awareness of a text, however, involves not only identifying the temporal expressions, but the events which these expressions anchor, as well as other events which must be ordered relative to them. Because of these broader concerns, TimeML has been developed as an annotation specification that encompasses not only temporal expressions, but all temporally relevant aspects of a text. The annotation schemes, however, are not interchangeable, resulting in incompatible corpora and accompanying extraction algorithms for each standard. In this paper, we describe an automatic migration process from the tags of TIDES to the tags of TimeML. This transformation procedure has been implemented and evaluated with two different corpora, obtaining 93.3 and 89.2% overall F-Measure respectively. [ABSTRACT FROM AUTHOR]

Real-time communication platforms such as ICQ, MSN and online chat rooms are getting more popular than ever on the Internet. There are, however, real risks where criminals and terrorists can perpetrate illegal and criminal abuses. This highlights the security significance of accurate detection and translation of the chat language to its stand language counterpart. The language used on these platforms differs significantly from the standard language. This language, referred to as chat language, is comparatively informal, anomalous and dynamic. Such features render conventional language resources such as dictionaries, and processing tools such as parsers ineffective. In this paper, we present the NIL corpus, a chat language text collection annotated to facilitate training and testing of chat language processing algorithms. We analyse the NIL corpus to study the linguistic characteristics and contextual behaviour of a chat language. First we observe that majority of the chat terms, i.e. informal words in a chat text, is formed by phonetic mapping. We then propose the eXtended Source Channel Model (XSCM) for the normalization of the chat language, which is a process to convert messages expressed in a chat language to its standard language counterpart. Experimental results indicate that the performance of XSCM in terms of chat term recognition and normalization accuracy is superior to its Source Channel Model (SCM) counterparts, and is also more consistent over time. [ABSTRACT FROM AUTHOR]

In a 12-month project we have developed a new, register-diverse, 55-million-word bilingual corpus—the New Corpus for Ireland (NCI)—to support the creation of a new English-to-Irish dictionary. The paper describes the strategies we employed, and the solutions to problems encountered. We believe we have a good model for corpus creation for lexicography, and others may find it useful as a blueprint. The corpus has two parts, one Irish, the other Hiberno-English (English as spoken in Ireland). We describe its design, collection and encoding. [ABSTRACT FROM AUTHOR]

This paper describes a corpus annotation project to study issues in the manual annotation of opinions, emotions, sentiments, speculations, evaluations and other private states in language. The resulting corpus annotation scheme is described, as well as examples of its use. In addition, the manual annotation process and the results of an inter-annotator agreement study on a 10,000-sentence corpus of articles drawn from the world press are presented. [ABSTRACT FROM AUTHOR]