Mona T. Diab
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Semantic Textual Similarity (STS) measures the degree of semantic equivalence between two texts. This paper presents the results of the STS pilot task in Semeval. The training data contained 2000… Expand
Semantic Textual Similarity (STS) measures the meaning similarity of sentences. Applications include machine translation (MT), summarization, generation, question answering (QA), short answer… Expand
In this paper, we present MADAMIRA, a system for morphological analysis and disambiguation of Arabic that combines some of the best aspects of two previously commonly used systems for Arabic… Expand
To date, there are no fully automated systems addressing the community's need for fundamental language processing tools for Arabic text. In this paper, we present a Support Vector Machine (SVM) based… Expand
In Semantic Textual Similarity (STS), systems rate the degree of semantic equivalence, on a graded scale from 0 to 5, with 5 being the most similar. This year we set up two tasks: (i) a core task… Expand
In Semantic Textual Similarity, systems rate the degree of semantic equivalence between two text snippets. This year, the participants were challenged with new data sets for English, as well as the… Expand
We present an overview of the first shared task on language identification on codeswitched data. The shared task included code-switched data from four language pairs: Modern Standard ArabicDialectal… Expand
Comunicacio presentada al 10th International Workshop on Semantic Evaluation (SemEval-2016), celebrat els dies 16 i 17 de juny de 2016 a San Diego, California.
In semantic textual similarity (STS), systems rate the degree of semantic equivalence between two text snippets. This year, the participants were challenged with new datasets in English and Spanish.… Expand
Although Subjectivity and Sentiment Analysis (SSA) has been witnessing a flurry of novel research, there are few attempts to build SSA systems for Morphologically-Rich Languages (MRL). In the current… Expand