Speaker
Affilliation
UPC Barcelona, visiting Sussex
Abstract
The Causal-State Splitting Reconstruction algorithm learns a finite state automaton from data sequences. In the work I will present, this algorithm is applied to NLP tasks, namely Named Entity Recognition and Chunking. The obtained results are slightly below the best state-of-the-arts system, but can be considered competitive, and given the simplicity of our approach, they are really promising.
Once the viability of using this algorithm for these NLP tasks is established, we plan to improve the results obtained at NER and Chunking by using more features, and also to study more sophisticated ways to use this algorithm in this kind of NLP tasks.