work needs to be done on the interface to make <term> users </term> aware of the increased
factors on which the <term> assessors </term> made their decisions . We tested this to see
to mark the <term> word </term> at which they made this decision . The results of this experiment
of the factors involved in the decision making process will be presented here . <term> Listen-Communicate-Show
<term> black-box OCR systems </term> in order to make it more useful for <term> NLP tasks </term>
in English . Typically , information that makes it to a summary appears in many different
over the <term> text </term> . Comparison is made against <term> non Bayesian summarizers </term>
within <term> reranking approaches </term> . We make use of a <term> conditional log-linear model
<term> model </term> learns to automatically make these assignments based on a <term> discriminative
<term> pronoun </term> , for which it does not make sense to look for an <term> antecedent </term>
<term> word segmentation problem </term> : it makes it possible to directly compare commercial
should benefit from the better predictions made by the <term> WSD models </term> . Using <term>
few years dramatic improvements have been made , and a number of comparative evaluations
The source code of the tool kit will be made available . This paper presents a <term>
from the <term> treebank </term> , and it would make the <term> treebank </term> more valuable as
that <term> semi-supervised methods </term> can make good use of small amounts of <term> labeled
enriching <term> speech recognition output </term> , making it easier for humans to read and downstream
InfoMagnets </term> . <term> InfoMagnets </term> aims at making exploratory <term> corpus analysis </term>
inferences </term> that a <term> listener </term> makes when a <term> verb </term> is used in a <term>
report a system <term> FROFF </term> which can make a fair copy of not only <term> texts </term>
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