Papers by Mark Sammons
On the Strength of Character Language Models for Multilingual Named Entity Recognition (D18-1)
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| Challenge: | Character-level patterns have been widely used in English Named Entity Recognition systems. |
| Approach: | They propose to use corpus-agnostic character-level language models to capture name tokens . they demonstrate they can capture name and non-name tokens in a diverse set of languages . |
| Outcome: | The proposed model improves the performance of an off-the-shelf NER system for multiple languages. |
CogCompNLP: Your Swiss Army Knife for NLP (L18-1)
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Daniel Khashabi, Mark Sammons, Ben Zhou, Tom Redman, Christos Christodoulopoulos, Vivek Srikumar, Nicholas Rizzolo, Lev Ratinov, Guanheng Luo, Quang Do, Chen-Tse Tsai, Subhro Roy, Stephen Mayhew, Zhili Feng, John Wieting, Xiaodong Yu, Yangqiu Song, Shashank Gupta, Shyam Upadhyay, Naveen Arivazhagan, Qiang Ning, Shaoshi Ling, Dan Roth
| Challenge: | a corpus-reader module supports popular corpora, feature extraction and annotation modules for semantic and syntactic tasks. |
| Approach: | They propose a library that provides modules to address different challenges . they provide a corpus-reader module that supports popular corpora in the NLP community . |
| Outcome: | The proposed library simplifies the process of design and development of NLP applications by providing modules to address different challenges. |