Learn More
In this paper we describe current efforts aimed at adapting an existing Question Answering system to a new document set, namely research papers in the genomics domain. The system has been originally developed for another restricted domain, however it has already proved its portability. Nevertheless, the process is not painless, and the specific purpose of(More)
INTRODUCTION In this paper, we describe the system used by the UMIST team as members of the FACILE consortium, to undertake the NE task in MUC-7. The main characteristics of this system employed are as follows: it is rule-based its rule formalism supports context-sensitive partial parsing rules may use pattern-matching-style iteration operators the notation(More)
A vast amount of scientific information is encoded in natural language text, and the quantity of such text has become so great that it is no longer economically feasible to have a human as the first step in the search process. Natural language processing and text mining tools have become essential to facilitate the search for and extraction of information(More)
BACKGROUND The biomedical domain is witnessing a rapid growth of the amount of published scientific results, which makes it increasingly difficult to filter the core information. There is a real need for support tools that 'digest' the published results and extract the most important information. RESULTS We describe and evaluate an environment supporting(More)
Attempto Controlled English (ACE) is a knowledge representation language with an English syntax. Thus ACE can be used by anyone, even without being familiar with formal notations. The At-tempto Parsing Engine translates ACE texts into discourse representation structures, a variant of first-order logic. Hence, ACE turns out to be a logic language equivalent(More)
We present Pro3Gres, a deep-syntactic, fast dependency parser that combines a handwritten competence grammar with proba-bilistic performance disambiguation and that has been used in the biomedical domain. We discuss its performance in the domain adaptation open submission. We achieve average results, which is partly due to difficulties in mapping to the(More)
BACKGROUND We report the Gene Normalization (GN) challenge in BioCreative III where participating teams were asked to return a ranked list of identifiers of the genes detected in full-text articles. For training, 32 fully and 500 partially annotated articles were prepared. A total of 507 articles were selected as the test set. Due to the high annotation(More)
BACKGROUND Determining usefulness of biomedical text mining systems requires realistic task definition and data selection criteria without artificial constraints, measuring performance aspects that go beyond traditional metrics. The BioCreative III Protein-Protein Interaction (PPI) tasks were motivated by such considerations, trying to address aspects(More)
BACKGROUND Research scientists and companies working in the domains of biomedicine and genomics are increasingly faced with the problem of efficiently locating, within the vast body of published scientific findings, the critical pieces of information that are needed to direct current and future research investment. RESULTS In this report we describe(More)