Learning to Disambiguate Syntactic Relations
AbstractNatural Language is highly ambiguous, on every level. This article describes a fast broad-coverage state-of-the-art parser that uses a carefully hand-written grammar and probability-based machine learning approaches on the syntactic level. It is shown in detail which statistical learning models based on Maximum-Likelihood Estimation (MLE) can support a highly developed linguistic grammar in the disambiguation process.
Schneider, G. (2013). Learning to Disambiguate Syntactic Relations. Linguistik Online, 17(5). https://doi.org/10.13092/lo.17.789