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We propose an enhanced Part-of-Speech (POS) tagger of Semitic languages that treats Modern Standard Arabic (henceforth Arabic) and Modern Hebrew (henceforth Hebrew) using the same probabilistic model and architectural setting. We start out by porting an existing Hidden Markov Model POS tagger for Hebrew to Arabic by exchanging a morphological analyzer for(More)
A major architectural decision in designing a disambiguation model for seg-mentation and Part-of-Speech (POS) tagging in Semitic languages concerns the choice of the input-output terminal symbols over which the probability distributions are defined. In this paper we develop a segmenter and a tagger for He-brew based on Hidden Markov Models (HMMs). We start(More)
We address Question Answering (QA) for biographical questions, i.e., questions asking for biographical facts about persons. The domain of biographical documents differs from other restricted domains in that the available collections of biographies are inherently incomplete: a major challenge is to answer questions about persons for whom biographical(More)
Current parameters of accurate unlexical-ized parsers based on Probabilistic Context-Free Grammars (PCFGs) form a two-dimensional grid in which rewrite events are conditioned on both horizontal (head-outward) and vertical (parental) histories. In Semitic languages, where arguments may move around rather freely and phrase-structures are often shallow, there(More)
We show that na¨ıve modeling of morphosyn-tactic agreement in a Constituency-Based (CB) statistical parsing model is worse than none, whereas a linguistically adequate way of modeling inflectional morphology in CB parsing leads to improved performance. In particular, we show that an extension of the Relational-Realizational (RR) model that incorporates(More)
A major challenge in statistical machine translation is mitigating the word order differences between source and target strings. While reordering and lexical translation choices are often conducted in tandem, source string permutation prior to translation is attractive for studying reordering using hierarchical and syntactic structure. This work contributes(More)
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