constituency parsing and dependency parsing 的区别

A constituency parse tree breaks a text into sub-phrases. Non-terminals in the tree are types of phrases, the terminals are the words in the sentence, and the edges are unlabeled. For a simple sentence "John sees Bill", a constituency parse would be: 句子 >> 短语们 Sentence | +-------------+------------+ | | Noun Phrase Verb Phrase | | John +-------+--------+ | | Verb Noun Phrase | | sees Bill A dependency parse connects words according to their relationships. Each vertex in the tree represents a word, child nodes are words that are dependent on the parent, and edges are labeled by the relationship. A dependency parse of "John sees Bill", would be: 句子 >> 关系(a, b) sees | +--------------+ subject | | object | | John Bill You should use the parser type that gets you closest to your goal. If you are interested in sub-phrases within the sentence, you probably want the constituency parse. If you are interested in the dependency relationships between words, then you probably want the dependency parse. The Stanford parser can give you either. In fact, the way it really works is to always parse the sentence with the constituency parser, and then, if needed, it performs a deterministic (rule-based) transformation on the constituency parse tree to convert it into a dependency tree. More can be found here: http://en.wikipedia.org/wiki/Phrase_structure_grammar http://en.wikipedia.org/wiki/Dependency_grammar