J13-3007 lattices impacts the performance of hypernym extraction . Given its higher performance
D10-1108 harvesting algorithm concerns hypernym extraction . Table 3 shows the total number
D10-1108 are automatically fed into the hypernym extraction phase . We use the natural order
D09-1097 . We conducted experiments on hypernym extraction targeting 694 words in the development
J13-3007 output . 2 . Definition & Hypernym Extraction ( Section 3.2 ) : Candidate definition
P10-1134 well-known approaches to definition and hypernym extraction . The paper is organized as follows
J13-3007 extraction and iterative definition and hypernym extraction . Second , we cope with issues
J13-3007 of definitional sentences and hypernym extraction . Our model is based on a formal
P10-1134 to the task of definition and hypernym extraction and compares favorably to other
J13-3007 assessment of the definition and hypernym extraction tasks in isolation was already
J13-3007 definition classification and hypernym extraction . 3.3 Domain Filtering and Creation
P07-2042 patterns to perform better on hypernym extraction than a combination of extraction
D12-1129 approaches could have been used for hypernym extraction from glosses ( Navigli and Velardi
P07-2042 . We compare our approach with hypernym extraction from morphological clues and
P07-2042 , 1998 ) for evaluation of our hypernym extraction methods . Hypernym-hyponym pairs
D09-1128 all synsets are considered for hypernym extraction . This is slightly different
D12-1129 the hypernyms extracted by our hypernym extraction technique in column 3 ) . b )
P10-1134 Word-Class Lattices for Definition and Hypernym Extraction </title> Navigli Velardi Abstract
D12-1129 glosses of t . We show an example of hypernym extraction for some terms in Table 1 ( we
J13-3007 that Kozareva and Hovy , during hypernym extraction , reject all the nodes not belonging
hide detail