Pattern-based unsupervised parsing method. (4th June 2014)

• Record Type: Journal Article
• Authors: SANTAMARÍA, JESÚS; ARAUJO, LOURDES
• Is Part Of: Natural language engineering. Volume 22:Part 3(2016)
• Page Start: 397
• Page End: 422
• Publication Date: 2014-06-04
• Subjects: Natural language processing (Computer science) -- Periodicals; Software engineering -- Periodicals; 006.35
• DOI: 10.1017/S1351324914000072
• Languages: English
• ISSNs: 1351-3249

Abstract

Abstract: We have developed a heuristic method for unsupervised parsing of unrestricted text. Our method relies on detecting certain patterns of part-of-speech tag sequences of words in sentences. This detection is based on statistical data obtained from the corpus and allows us to classify part-of-speech tags into classes that play specific roles in the parse trees. These classes are then used to construct the parse tree of new sentences via a set of deterministic rules. Aiming to asses the viability of the method on different languages, we have tested it on English, Spanish, Italian, Hebrew, German, and Chinese. We have obtained a significant improvement over other unsupervised approaches for some languages, including English, and provided, as far as we know, the first results of this kind for others.