Claire Nedellec

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The BioNLP Shared Task 2013 is the third edition of the BioNLP Shared Task series that is a community-wide effort to address fine-grained, structural information extraction from biomedical literature. The BioNLP Shared Task 2013 was held from January to April 2013. Six main tasks were proposed. 38 final submissions were received, from 22 teams. The results(More)
We describe in this paper the ML system, ASIUM, which learns subcategorization frames of verbs and ontologies from syntactic parsing of technical texts in natural language. The restrictions of selection in the subcategorization frames are filled by the concepts of the ontology. Applications requiring subcategorization frames and ontologies are crucial and(More)
In this paper, we describe the Machine Learning system, asium 1 , which learns Subcaterorization Frames of verbs and ontologies from the syntactic parsing of technical texts in natural language. The restrictions of selection in the subcategorization frames are lled by the ontology's concepts. Applications requiring such knowledge are crucial and numerous.(More)
This paper describes Mo’K, a configurable workbench that supports the development of conceptual clustering methods for ontology building. Mo’K is intended to assist ontology developers in the exploratory process of defining the most suitable learning methods for a given task. To do so, it provides facilities for evaluation, comparison, characterization and(More)
We present the BioNLP 2011 Shared Task Bacteria Track, the first Information Extraction challenge entirely dedicated to bacteria. It includes three tasks that cover different levels of biological knowledge. The Bacteria Gene Renaming supporting task is aimed at extracting gene renaming and gene name synonymy in PubMed abstracts. The Bacteria Gene(More)
This paper presents the Bacteria Biotope task of the BioNLP Shared Task 2013, which follows BioNLP-ST-11. The Bacteria Biotope task aims to extract the location of bacteria from scientific web pages and to characterize these locations with respect to the OntoBiotope ontology. Bacteria locations are crucial knowledge in biology for phenotype studies. The(More)
This paper presents the Bacteria Biotope task as part of the BioNLP Shared Tasks 2011. The Bacteria Biotope task aims at extracting the location of bacteria from scientific Web pages. Bacteria location is a crucial knowledge in biology for phenotype studies. The paper details the corpus specification, the evaluation metrics, summarizes and discusses the(More)
We present the two Bacteria Track tasks of BioNLP 2013 Shared Task (ST): Gene Regulation Network (GRN) and Bacteria Biotope (BB). These tasks were previously introduced in the 2011 BioNLP-ST Bacteria Track as Bacteria Gene Interaction (BI) and Bacteria Biotope (BB). The Bacteria Track was motivated by a need to develop specific BioNLP tools for fine-grained(More)
The goal of the Genic Regulation Network task (GRN) is to extract a regulation network that links and integrates a variety of molecular interactions between genes and proteins of the well-studied model bacterium Bacillus subtilis. It is an extension of the BI task of BioNLP-ST’11. The corpus is composed of sentences selected from publicly available PubMed(More)