Жергілікті контекст

The classification information model or CIM classi- fies instances by considering the discrimination abil- ity of their features, which was proven to be useful for word sense disambiguation at SENSEVAL-1. …...

In this work we propose a transla- tion model for monolingual sentence retrieval. We propose four methods for constructing a parallel corpus. Of the four methods proposed, a lexi- con …...

As it serves as a basis for POS tagging, cat- egory induction, and human category ac- quisition, we investigate the information needed to disambiguate a word in a lo- cal …...

Information Extraction (IE) systems that extract role fillers for events typically look at the local context surrounding a phrase when deciding whether to extract it. Of- ten, however, role fillers …...

Computational approaches to metonymy res- olution have focused almost exclusively on the local context, especially the constraints placed on a potentially metonymic word by its grammatical collocates. We expand such …...

We introduce an extension to the bag-of- words model for learning words represen- tations that take into account both syn- tactic and semantic properties within lan- guage. This is done …...

AbstractWhen reading a text, it is common to become stuck on unfamiliar words and phrases, such as polysemous words with novel senses, rarely used idioms, internet slang, or emerging entities. …...

AbstractIrrespective of the success of the deep learning-based mixed-domain transfer learning approach for solving various Natural Language Processing tasks, it does not lend a generalizable solution for detecting misinformation from …...