Automatic Syntactic Analysis Based on Selectional Preferences
Gelbukh, Alexander
Automatic Syntactic Analysis Based on Selectional Preferences by Alexander Gelbukh, Hiram Calvo. - 1 recurso en línea (VIII, 165 páginas) - Studies in Computational Intelligence 765 1860-949X Engineering (Springer-11647) .
Introduction -- First approach: sentence analysis using rewriting rules -- Second approach: constituent grammars -- Third approach: dependency trees -- Evaluation of the dependency parser -- Applications -- Prepositional phrase attachment disambiguation -- The unsupervised approach: grammar induction -- Multiple argument handling -- The need for full co-occurrence.
This book describes effective methods for automatically analyzing a sentence, based on the syntactic and semantic characteristics of the elements that form it. To tackle ambiguities, the authors use selectional preferences (SP), which measure how well two words fit together semantically in a sentence. Today, many disciplines require automatic text analysis based on the syntactic and semantic characteristics of language and as such several techniques for parsing sentences have been proposed. Which is better? In this book the authors begin with simple heuristics before moving on to more complex methods that identify nouns and verbs and then aggregate modifiers, and lastly discuss methods that can handle complex subordinate and relative clauses. During this process, several ambiguities arise. SP are commonly determined on the basis of the association between a pair of words. However, in many cases, SP depend on more words. For example, something (such as grass) may be edible, depending on who is eating it (a cow?). Moreover, things such as popcorn are usually eaten at the movies, and not in a restaurant. The authors deal with these phenomena from different points of view.
9783319740546
10.1007/978-3-319-74054-6 doi
Traductores
Q342 EB
Automatic Syntactic Analysis Based on Selectional Preferences by Alexander Gelbukh, Hiram Calvo. - 1 recurso en línea (VIII, 165 páginas) - Studies in Computational Intelligence 765 1860-949X Engineering (Springer-11647) .
Introduction -- First approach: sentence analysis using rewriting rules -- Second approach: constituent grammars -- Third approach: dependency trees -- Evaluation of the dependency parser -- Applications -- Prepositional phrase attachment disambiguation -- The unsupervised approach: grammar induction -- Multiple argument handling -- The need for full co-occurrence.
This book describes effective methods for automatically analyzing a sentence, based on the syntactic and semantic characteristics of the elements that form it. To tackle ambiguities, the authors use selectional preferences (SP), which measure how well two words fit together semantically in a sentence. Today, many disciplines require automatic text analysis based on the syntactic and semantic characteristics of language and as such several techniques for parsing sentences have been proposed. Which is better? In this book the authors begin with simple heuristics before moving on to more complex methods that identify nouns and verbs and then aggregate modifiers, and lastly discuss methods that can handle complex subordinate and relative clauses. During this process, several ambiguities arise. SP are commonly determined on the basis of the association between a pair of words. However, in many cases, SP depend on more words. For example, something (such as grass) may be edible, depending on who is eating it (a cow?). Moreover, things such as popcorn are usually eaten at the movies, and not in a restaurant. The authors deal with these phenomena from different points of view.
9783319740546
10.1007/978-3-319-74054-6 doi
Traductores
Q342 EB