| N03-1023 | assumes a parametric model of | data generation | . The labels of the unlabeled |
| J87-1020 | items are statically defined at | data generation | time , the LKB extracts relationships |
| C02-1130 | consequence of using this method for | data generation | is that the training set created |
| D15-1203 | 1 , the algorithm for training | data generation | is sometimes faced with the wrong |
| D13-1183 | information as a coarse filter in the | data generation | stage , they still largely rely |
| P02-1045 | feature ) . 4.3 Test and Training | Data Generation | From our annotated corpus , we |
| C02-1130 | selection , but also a better | data generation | procedure . In future work , |
| P09-1120 | systematic and collaborative study . 3 | Data Generation | We start the construction of |
| M92-1001 | Focus on the Issue of Spurious | Data Generation | The MUC-3 measures of performance |
| P11-1055 | relation-independent and relation-specific . 6.1 | Data Generation | We used the same data sets as |
| P03-1022 | resolution in written text . 3.2 | Data Generation | Training and test data instances |
| D12-1045 | Section 3.3 and , just like the | data generation | loop in Algorithm 2 , creates |
| N09-2032 | system-driven dialogue by artificial | data generation | . Our main contribution lies |
| C02-1130 | . The failure of our automatic | data generation | algorithm to produce a good sample |
| D11-1076 | in the candidate and training | data generation | steps . 5 Related Work Using |
| P10-2066 | image retrieval application . 3 | Data Generation | for Distributional Similarity |
| P10-1096 | sampling as a separate step from the | data generation | process , in which we can formulate |
| N09-2032 | artificial corpus will be NP NSUs .3 4 | Data generation | We constructed our artificial |
| D13-1086 | described in section 2.1 . In training | data generation | , we choose top 10 % similar |
| M91-1001 | generation combines with incorrect | data generation | to affect the precision score |
