Protein names and how to find them.
A prerequisite for all higher level information extraction tasks is the identification of unknown names in text. Today, when large corpora can consist of billions of words, it is of utmost importance to develop accurate techniques for the automatic detection, extraction and categorization of named entities in these corpora. Although named entity recognition might be regarded a solved problem in some domains, it still poses a significant challenge in others. In this work we focus on one of the more difficult tasks, the identification of protein names in text. This task presents several interesting difficulties because of the named entities variant structural characteristics, their sometimes unclear status as names, the lack of common standards and fixed nomenclatures, and the specifics of the texts in the molecular biology domain in which they appear. We describe how we approached these and other difficulties in the implementation of Yapex, a system for the automatic identification of protein names in text. We also evaluate Yapex under four different notions of correctness and compare its performance to that of another publicly available system for protein name recognition.
Franzén
Kristofer
K
Swedish Institute of Computer Science, Box 1263, SE-164 29, Kista, Sweden. franzen@sics.se
Eriksson
Gunnar
G
Olsson
Fredrik
F
Asker
Lars
L
Lidén
Per
P
Cöster
Joakim
J
D004014:Dictionaries as Topic; D006801:Humans; D016247:Information Storage and Retrieval; D008037:Linguistics; D008490:Medical Informatics; D008967:Molecular Biology; D009275:Names; D009323:Natural Language Processing; D011506:Proteins
D011506:Proteins