Tense Tagging for Verbs in Cross-Lingual Context: A Case Study

The current work applies Conditional Random Fields to the problem of temporal reference mapping from Chinese text to English text. The learning algorithm utilizes a moderate number of linguistic features that are easy and inexpensive to obtain. We train a tense classifier upon a small amount of manually labeled data. The evaluation results are promising according to standard measures as well as in comparison with a pilot tense annotation experiment involving human judges. Our study exhibits potential value for full-scale machine translation systems and other natural language processing tasks in a crosslingual scenario.

• Type: Conference
• Year: 2005
• Where: IJCNLP
• Authors: Yang Ye, Zhu Zhang
• Keywords: Conditional Random Fields, IJCNLP 2005, Natural Language Processing, Temporal Reference Mapping, Tense Classifier