We present a novel algorithm for multilingual dependency parsing that uses annotations from a diverse set of source languages to parse a new unannotated language. Our motivation i...
Most previous work on multilingual sentiment analysis has focused on methods to adapt sentiment resources from resource-rich languages to resource-poor languages. We present a nov...
Bin Lu, Chenhao Tan, Claire Cardie, Benjamin K. Ts...
Most previous studies of morphological disambiguation and dependency parsing have been pursued independently. Morphological taggers operate on n-grams and do not take into account...
Verb suffixes and verb complexes of morphologically rich languages carry a lot of information. We show that this information if harnessed for the task of shallow parsing can lead ...
Harshada Gune, Mugdha Bapat, Mitesh M. Khapra, Pus...
We illustrate and explain problems of n-grams-based machine translation (MT) metrics (e.g. BLEU) when applied to morphologically rich languages such as Czech. A novel metric SemPO...
In this paper we report our work on building a POS tagger for a morphologically rich language- Hindi. The theme of the research is to vindicate the stand that- if morphology is st...
We address the problem of translating from morphologically poor to morphologically rich languages by adding per-word linguistic information to the source language. We use the synt...