The SEER project is funded by the Edinburgh-Stanford link. The personnel in Edinburgh are Beatrice Alex, Shipra Dingare, Claire Grover, Ben Hachey, Ewan Klein, Yuval Krymolowski, Katja Markert and Malvina Nissim. The personnel in Stanford are Chris Manning, Joseph Smarr, Huy Nguyen, and Jenny Finkel.
This project will extend and generalise the current state-of-the-art in entity recognition so that it can become a reliable enabling technology for a wide range of applications and higher-level NLP tasks. Our goal is to develop the means to recognize and classify a much wider range of entities than are traditionally treated, and to develop techniques which can be applied in a wide range of text types. Rapid adaptation to new domains is a priority and this requires modularity in the processing pipeline as well as the innovative use of machine-learning techniques to enable the use of unnannotated corpora as training material wherever possible.
Specific objectives include:
Named Entity Recognition (NER) technology is an essential ingredient in Information Extraction (IE) and there are a number of commercial IE systems currently available. Clearly, our improvements on current NER technology would be of immediate benefit to builders of such systems. However, more broadly it has the potential to support a variety of applications which require domain-specific semantic information while not requiring full Natural Language Understanding.
Jenny Finkel, Shipra Dingare, Christopher Manning, Malvina Nissim, Beatrice Alex, and Claire Grover. in press. Exploring the Boundaries: Gene and Protein Identification in Biomedical Text. BMC Bioinformatics 6 (Suppl 1). [pdf]
Ben Hachey, Beatrice Alex and Markus Becker. 2005. Investigating the Effects of Selective Sampling on the Annotation Task. In: Proceedings of the 9th Conference on Computational Natural Language Learning, Ann Arbor, Michigan, USA. [pdf]
Markus Becker, Ben Hachey, Beatrice Alex and Claire Grover. 2005. Optimising Selective Sampling for Bootstrapping Named Entity Recognition. In: Proceedings of the ICML-2005 Workshop on Learning with Multiple Views, Bonn, Germany. [pdf]
Beatrice Alex. 2005. An Unsupervised System for Identifying English Inclusions in German Text. In Proceedings of the 43rd Annual Meeting of the Association for Computational Linguistics (ACL 2005) - Student Research Workshop. Ann Arbor, Michigan. [pdf]
Shipra Dingare, Jenny Finkel, Malvina Nissim, Christopher Manning and Claire Grover. 2004. A System For Identifying Named Entities in Biomedical Text: How Results From Two Evaluations Reflect on Both the System and the Evaluations. In The 2004 BioLink meeting: Linking Literature, Information and Knowledge for Biology at ISMB 2004. Republished as Shipra Dingare, Malvina Nissim, Jenny Finkel, Christopher Manning and Claire Grover. 2005. Comparative and Functional Genomics 6: 77-85. [pdf]
Jenny Finkel, Shipra Dingare, Huy Nguyen, Malvina Nissim, Christopher Manning and Gail Sinclair. 2004. Exploiting Context for Biomedical Entity Recognition: From Syntax to the Web. In Proceedings of the Joint Workshop on Natural Language Processing in Biomedicine and its Applications at Coling 2004. [pdf]
Shipra Dingare, Jenny Finkel, Christopher Manning, Malvina Nissim and Beatrice Alex. 2004. Exploring the Boundaries: Gene and Protein Identification in Biomedical Text. Proceedings of the BioCreative Workshop, Granada. [pdf]
Ben Hachey, Huy Nguyen, Malvina Nissim, Beatrice Alex and Claire Grover. 2004. Grounding Gene Mentions with Respect to Gene Database Identifiers. Proceedings of the BioCreative Workshop, Granada. [pdf]
Yuval Krymolowski, Beatrice Alex, and Jochen L. Leidner. 2004. BioCreative Task 2.1: The Edinburgh-Stanford System. Proceedings of the BioCreative Workshop, Granada. [pdf]
Beatrice Alex and Claire Grover. 2004. An XML-based Tool for Tracking English Inclusions in German Text. In PAPILLON 2004 Workshop on Multilingual Lexical Databases, Grenoble, France. [pdf]
Malvina Nissim, Colin Matheson and James Reid. 2004. Recognising Geographical Entities in Scottish Historical Documents. Proceedings of the Workshop on Geographic Information Retrieval at SIGIR 2004. [pdf]