{"id":290,"date":"2017-09-25T11:47:32","date_gmt":"2017-09-25T09:47:32","guid":{"rendered":"https:\/\/user.phil.hhu.de\/kallmeyer\/?page_id=290"},"modified":"2018-02-16T11:13:25","modified_gmt":"2018-02-16T10:13:25","slug":"parsing-winter-1718","status":"publish","type":"page","link":"https:\/\/user.phil.hhu.de\/kallmeyer\/teaching\/parsing-winter-1718\/","title":{"rendered":"Parsing – Winter 17\/18"},"content":{"rendered":"

Seminar (Laura Kallmeyer)<\/h4>\n

Monday 10.30-12.00 and Tuesday 08.30-10.00, room 24.53.01.81.<\/p>\n

Start: 09.10.2017. Last session: 30.01.2018.<\/p>\n

Course description:<\/h4>\n

Parsing is a central task in natural language processing. Its goal is to compute the syntactic structures of sentences. Such a syntactic structure could either be a constituency structure or a dependency structure. The former is in many cases taken to be generated by a context-free grammar (CFG). Consequently, constituency parsing amounts to a) implementing\/inducing a context-free grammar and b) using this grammar for parsing. Dependency parsing, in contrast to this, is mostly grammar-less parsing using machine-learning techniques. <\/p>\n

In this course, we will mainly concentrate on step b) of CFG-based constituency parsing. We will revise various symbolic parsing algorithms that yield, given a CFG and an input sentence, the set of all parse trees for this sentence. In the second half of the course, we will move on to probabilistic parsing, covering Viterbi parsing and weighted deductive parsing with A* estimates.<\/p>\n

For references see the slides of the individual sessions. <\/p>\n

Schedule and Slides<\/h4>\n
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