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As someone who has published work in the NLP area, I always take claimed results with a grain of salt. With that said, I still will have to read the paper to know the implementation details, although my problem with generic linguistic approaches such as this one seems to be is that it is usually hard to "port" to other languages. For instance, the way they parse sequences of words may or may not be too specific to the English language. It is somewhat similar to what we call "overfitting" in the data-mining area, and it may invalidate this technique for other languages. When I worked on this area (up to 2014), I worked mainly in language-independent statistical approaches. As with everything, it has its cons as you can extract information from more languages, but, in general, with less certainties. But in general, it is good to see that the NLP area is still alive somewhere, as I can't seem to find any NLP jobs where I live! :) Edit: I've read it in the diagonal, and it is based on a Neural Network, so in theory, if it was trained in other languages, it could return good enough results as well. It is normal for English/American authors to include only english datasets, but I would like to see an application to another language.. This is a very specialized domain of knowledge, so I'm quite limited on my analysis.. |
Nlp is very much alive and well.