Abstract
Named Entity Recognition(NER) is an important topic in NLP, and it is the foundation for many advanced NLP topics. Many mature tools have been implemented (e.g. spaCy, Stanford CoreNLP), but their performance is quite limited in specific domains.
Cooperating with INTELLLEX (A Tech Start-up For Law), we are focusing on a NER in legal domain. We aim to increase precision of existing Named Entity(NE) types(e.g. Person, Location, Org), and train new NE types for the feature of legal domain(e.g. Law).
The NER we’re building will be the foundation of many advanced NLP topics, like Relation Extraction and Topic Prediction, which will contribute to a better legal search engine!
Members
- [insert_php] echo get_avatar( $id_or_email=’miaoyisong@gmail.com’, $size=30 ); [/insert_php] Yisong Miao (Undergraduate Intern)
Yanchuan Sim (Co-Supervisor from INTELLLEX)- [insert_php] echo get_avatar( $id_or_email=’cmkumar087@gmail.com’, $size=30 ); [/insert_php] Kishaloy Halder (Graduate Students)
- [insert_php] echo get_avatar( $id_or_email=’kanmy@comp.nus.edu.sg’, $size=30 ); [/insert_php] Min-Yen Kan (Advisor and Professor)
Documents
Internship Reports, 31st Aug.