- Tytuł:
- Text : now in 2D! A framework for lexical expansion with contextual similarity
- Autorzy:
-
Biemann, C.
Riedl, M. - Powiązania:
- https://bibliotekanauki.pl/articles/103919.pdf
- Data publikacji:
- 2013
- Wydawca:
- Polska Akademia Nauk. Instytut Podstaw Informatyki PAN
- Tematy:
-
distributional semantics
lexical expansion
contextual similarity
lexical substitution
computational semantics - Opis:
- A new metaphor of two-dimensional text for data-driven semantic modeling of natural language is proposed, which provides an entirely new angle on the representation of text: not only syntagmatic relations are annotated in the text, but also paradigmatic relations are made explicit by generating lexical expansions. We operationalize distributional similarity in a general framework for large corpora, and describe a new method to generate similar terms in context. Our evaluation shows that distributional similarity is able to produce high-quality lexical resources in an unsupervised and knowledge-free way, and that our highly scalable similarity measure yields better stores in a WordNet-based evaluation than previous measures for very large corpora. Evaluating on a lexical substitution task, we find that our contextualization method improves over a non-contextualized baseline across all parts of speech, and we show how the metaphor can be applied successfully to part-of-speech tagging. A number of ways to extend and improve the contextualization method within our Framework are discussed. As opposed to comparable approaches, our framework defines a model of lexical expansions in context that can generate the expansions as opposed to ranking a given list, and thus does not require existing lexical-semantic resources.
- Źródło:
-
Journal of Language Modelling; 2013, 1, 1; 55-95
2299-856X
2299-8470 - Pojawia się w:
- Journal of Language Modelling
- Dostawca treści:
- Biblioteka Nauki
Artykuł