| model,1-6-H05-1064,ak | The <term> model </term> gives an <term> F-measure improvement </term> of [ ? ] 1.25 % beyond the <term> base parser </term> , and an [ ? ] 0.25 % improvement beyond the <term> Collins ( 2000 ) reranker </term> . | #5528 The model gives an F-measure improvement of [?] 1.25% beyond the base parser, and an [?] 0.25% improvement beyond the Collins (2000) reranker. | |
| model,1-3-H05-1064,ak | The <term> model </term> learns to automatically make these assignments based on a <term> discriminative training criterion </term> . | #5471 The model learns to automatically make these assignments based on a discriminative training criterion. | |
| model,5-4-H05-1064,ak | <term> Training </term> and <term> decoding </term> with the <term> model </term> requires summing over an exponential number of hidden-variable assignments : the required summations can be computed efficiently and exactly using <term> dynamic programming </term> . | #5490 Training and decoding with the model requires summing over an exponential number of hidden-variable assignments: the required summations can be computed efficiently and exactly using dynamic programming. | |
| model,8-5-H05-1064,ak | As a case study , we apply the <term> model </term> to <term> parse reranking </term> . | #5522 As a case study, we apply the model to parse reranking. |
