[PDF] Top 20 Statistical Models for Unsupervised Prepositional Phrase Attachment

... Heuristic Extraction of Unambiguous Cases Given a tagged and chunked sentence, the extraction heuristic returns head word tuples of the form v,p, n2 or n,p, n2, where v is the verb, n is[r] ... See full document

... Statistical Models for Unsupervised Prepositional Phrase Attachment S t a t i s t i c a l M o d e l s for U n s u p e r v i s e d P r e p o s i t i o n a l P h r a s e A t t a c h m e n t A d w a i t[.] ... See full document

... Prepositional phrase attachment is an im- portant subproblem of parsing, performance on which suffers from limited availability of labelled ...of models will be interesting to com- bine using ... See full document

... PP attachment module using supervised machine learning techniques, integrated as a module within a shallow parser, and reach state of the art accuracy when com- paring to one of the best statistical parsers ... See full document

... PP attachment based on corpus co-occurrence statistics, gathered either from manually annotated training data (Collins and Brooks, 1995; Brill and Resnik, 1994) or from automatically acquired training data that ... See full document

... in phrase (1) as a tool for eating. Current statistical methods, dominant in the field of syntactic analysis, take into account selectional restrictions implicitly by assigning the most probable syntactic ... See full document

... The Bikel parser’s performance (without changing attachments) is slightly lower than C&B’s, O&M’s, and TM&N’s. However, for the trilexical case, the difference is not statistically significant for NA-discard. ... See full document

... The need for going beyond a single vector per word-type has been well established for a while, and many efforts were focused on building multi-prototype vector space models of meaning (Reisinger and Mooney, 2010; ... See full document

... Unlike Zhao and Lin, and many other authors tackling this problem using the Penn Treebank, our model is unsupervised and generative. The first fact makes more data available for training, since we can learn from ... See full document

... PP attachment. In general, the results that our models obtain are remarkably good, despite the fact that we only combine word embeddings in a straightforward ... See full document

... Minimal Attachment account for more than 55% of cases — the actual attachment ratio depends on the corpus — and work by Taraban and McClel- land (1990) showed that these structural models are poor ... See full document

... languages annotated for specific tasks and representations, providing complete coverage for the vast array of domains and genres that require language processing tools is an im- mense challenge. However, it has been ... See full document

... The state of the art is a supervised algorithm that employs a semantically tagged corpus (Stetina and Nagao, 1997). Each word in a labelled corpus is sense-tagged using an unsupervised word-sense disambiguation ... See full document

... The Model Switch- ing method as proposed in this paper can be used with any utility function decision criterion for any decision problem with categorical d a t a that can be represented [r] ... See full document

... Matt Post et al [8] described the collection of six parallel corpora containing four-way redundant translations of the source-language text. The Indian languages of these corpora are low-resource and understudied, and ... See full document

... In addition to developing an unsupervised CP disambiguation model, In [MG, in prep] we have developed two supervised models one backed-off and one maximum entropy for determining CP atta[r] ... See full document

... The best performing systems for many tasks in natural language processing are based on su- pervised training on annotated corpora such as the Penn Treebank (Marcus et al., 1993) and the prepositional phrase ... See full document

... Probabilistic models have been effective in re- solving prepositional phrase attachment am- biguity, but sparse data remains a significant ...PP attachment model and we obtain ... See full document

... capture the full dimensionality of the word vectors. A second type of features induced from raw data that we consider are Brown clusters, which were found to be useful in dependency parsing (Koo et al., 2008). Compared ... See full document

... Using a parallel presentation it is also possible to detect complex interactions between the classes of a particular sense for example, exceptions or the classes of different senses that[r] ... See full document