Traditionally, research in identifying structured entities in documents has proceeded independently of document categorization research. In this paper, we observe that these two t...
We consider the problem of improving named entity recognition (NER) systems by using external dictionaries--more specifically, the problem of extending state-of-the-art NER system...
Due to the lack of annotated data sets, there are few studies on machine learning based approaches to extract named entities (NEs) in clinical text. The 2009 i2b2 NLP challenge is...
In this paper, we present HeiNER, the multilingual Heidelberg Named Entity Resource. HeiNER contains 1,547,586 disambiguated English Named Entities together with translations and ...
Wolodja Wentland, Johannes Knopp, Carina Silberer,...
This paper describes a new scoring algorithm that supports comparison of linguistically annotated data from noisy sources. The new algorithm generalizes the Message Understanding ...
John D. Burger, David D. Palmer, Lynette Hirschman