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Proceedings of the Ninth International Conference on Computational Semantics (IWCS 2011)

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Figure

Figure 1: General-purpose functions
Table 3: Formal labels for an example sentence.
Figure 1: Construction of a multilingual vector (combinations of target languages C(3, k), where k = 0..3
Table 3: Aggregate accuracies obtained on the TWA and SEMEVALmicro-accuracy obtained when using the most common sense (MCS),the multinomial Na¨ıve Bayes classifier on binary weighted monolingual features in English, datasets; Columns: 1 - dataset, 2 - average 3 - average micro-accuracy obtained using 4 - 7 - average micro-accuracy computed over all possible combinations of English and 3 languages taken 0 through 3 at a time, resultedfrom features weighted following a modified normal distribution with σ2 = 5 and an amplification factor of 20using a multinomial Na¨ıve Bayes learner, where 4 - one language, 5 - 2 languages, 6 - 3 languages, 7 - 4 languages,8 - error reduction calculated between ND-L1 (4) and ND-L4 (7)
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