An automatic compound retrieval method is proposed to extract compounds within a text message. It uses n-gram mutual information, relative frequency count and parts of speech as t...
Most natural language processing tasks require lexical semantic information. Automated acquisition of this information would thus increase the robustness and portability of NLP sy...
We present an algorithm for computing n-gram probabilities from stochastic context-free grammars, a procedure that can alleviate some of the standard problems associated with n-gr...
We present a stochastic finite-state model for segmenting Chinese text into dictionary entries and productively derived words, and providing pronunciations for these words; the me...
Richard Sproat, Chilin Shih, William Gale, Nancy C...
This paper describes an on-going study which applies the concept of transitivity to news discourse for text processing tasks. The complex notion of transitivity is defined and the...
Wepresent a new approachtodisambiguatingsyntactically ambiguous words in context, based on Variable Memory Markov (VMM) models. In contrast to xed-length Markovmodels,whichpredict...
I examine how terminological languages can be used to manage linguistic data during NL research and development. In particular, I consider the lexical semantics task of characteri...