BibSonomy publications for /user/diego_ma/annotation question_answeringFri Dec 14 02:41:25 CET 2007Proc. ODBASE 2002Natural Language Annotations for the Semantic Web2002question_answering semantic_web annotation Because the ultimate purpose of the Semantic Web is to help users locate, organize, and process information, we strongly believe that it should be grounded in the information access method humans are most comfortable with ---natural language. However, the Resource Description Framework (RDF), the foundation of the Semantic Web, was designed to be easily processed by computers, not humans. To render RDF friendlier to humans, we propose to augment it with natural language annotations, or metadata written in everyday language. We argue that natural language annotations are not only intuitive and e.ective, but can also accelerate the pace with which the Semantic Web is being adopted. We demonstrate the use of natural language annotations from within Haystack, an end user Semantic Web platform that also serves as a testbed for our ideas. In addition to a prototype SemanticWeb question answering system, we describe other opportunities for marrying natural language and Semantic Web technology.Fri Dec 14 02:38:00 CET 2007Proc. EACL 2003 workshop on NLP for Question Answering13-19Generating Annotated Corpora for Reading Comprehension and Question Answering Evaluation.2003annotation question_answering Recently, reading comprehension tests for students and adult language learners have received increased attention within the NLP community as a means to develop and evaluate robust question answering (NLQA) methods. We present our ongoing work on automatically creating richly annotated corpus resources for NLQA and on comparing automatic methods for answering questions against this data set. Starting with the CBC4Kids corpus, we have added XML annotation layers for tokenization, lemmatization, stemming, semantic classes, POS tags and best anking syntactic parses to support future experiments with semantic answer retrieval and inference. Using this resource, we have calculated a baseline for word-overlap based answer retrieval (Hirschman et al., 1999) on the CBC4Kids data and found the method performs slightly better than on the REMEDIA corpus. We hope that our richly annotated version of the CBC4Kids corpus will become a standard resource, especially as a controlled environment for evaluating inference-based techniques.