| W15-2921 | verbs for open-domain opinion | role extraction | . This raises the question whether |
| W15-2921 | of the current state of opinion | role extraction | involving opinion verbs . We |
| K15-1022 | Work Most approaches for opinion | role extraction | employ supervised learning . |
| W15-2921 | Yet little research on opinion | role extraction | has actually paid attention to |
| P04-1055 | semantic relation classification and | role extraction | from bioscience text . The methods |
| P04-1055 | work While there is much work on | role extraction | , very little work has been done |
| C02-2011 | develop a general model for case | role extraction | . The idea is to learn domain-independent |
| P04-1055 | not help much for the task of | role extraction | , they did help for relation |
| K15-1022 | verbs into three types for opinion | role extraction | . 5.2 In-Context Evaluation We |
| P04-1055 | below . For the evaluation of the | role extraction | task , we calculate the usual |
| P04-1055 | relevant " were similar . For the | role extraction | task , the most important feature |
| P04-1055 | number of roles ( three ) for the | role extraction | task . The network was trained |
| K15-1022 | classification . 2 Lexicon-based Opinion | Role Extraction | Opinion holder and target extraction |
| S12-1016 | tree as the basis of the semantic | role extraction | ; we assumed that every semantic |
| H05-1092 | interaction classification ( and | role extraction | ) . A hand-assessment of the |
| P04-1055 | relation classification and 1.4 % for | role extraction | ( in the " only relevant " , |
| H05-1092 | protein name tagging ( also known as | role extraction | ) : the task consists of identifying |
| P04-1055 | Craven ( 2001 ) however , the | role extraction | task is quite similar to ours |
| P04-1055 | " case ) , 7.4 % and 7.3 % for | role extraction | and 27.1 % and 44 % for relation |
| P04-1055 | HMM-like graphical models for | role extraction | ( Bikel et al. , 1999 ; Freitag |
