Question answering systems can be seen as the next step in information retrieval, allowing users to pose questions in natural language and receive succinct answers. In order for a question answering system as a whole to be successful, research has shown that the correct classification of questions with regards to the expected answer type is imperative. Question classification has two components...

The queries to a practical Question Answering (QA) system range from keywords, phrases, badly written questions, and occasionally grammatically perfect questions. Among different kinds of question analysis approaches, the pattern matching works well in analyzing such queries. It is costly to build this pattern matching module because tremendous manual labor is needed to expand its coverage to s...

This paper reports the most significant issues related to the launching of a Monolingual Spanish Question Answering evaluation track at the Cross Language Evaluation Forum (CLEF 2003). It introduces some questions about multilingualism and describes the methodology for test suite production, task, judgment of answers as well as the results obtained by the participant systems.

We present SFS-QA, an automatic realtime question-answering system, that can answer free-text questions within a minute. SFS-QA system analyzes a question and transforms it into a boolean keyword query using Stanford Dependency Parser and MetaMap tagger. The query is used to obtain matching web pages from the World Wide Web through Google Search API. In addition, two specific data sources: Yaho...

The recent developments in Question Answering have kept with open-domain questions and collections, sometimes argued as being more difficult than narrow domain-focused questions and corpora. The biomedical field is indeed a specialized domain; however, its scope is fairly broad, so that considering a biomedical QA task is not necessarily such a simplification over open-domain QA as represented ...

Machine comprehension, an unsolved problem in machine learning, enables a machine to process a passage and answer associated questions with a high level of accuracy that matches human performance. We use the SQuAD dataset, which simplifies the question-answer process, where the answer is defined by the starting and ending indices of its location in the context paragraph. In this paper, we explo...

INTRODUCTION Data-driven methods have proven to be powerful techniques for natural language processing. It is still unclear to what extent this success can be attributed to specific techniques, versus simply the data itself. For example, in [Banko and Brill 2001] it was demonstrated that for confusion set disambiguation, a prototypical disambiguation-instring-context problem, the amount of data...

The n a t u r a l language d a t a b a s e query system i n c o r p o r a t e d in the KNOBS i n t e r a c t i v e p l a n n i n g sys t em compr i ses a d i c t i o n a r y d r i v e n p a r s e r , APE-II , and s c r i p t i n t e r p r e t e r which y i e l d a c o n c e p t u a l dependency c o n c e p t u a l i z a t i o n as a r e p r e s e n t a t i o n of the manning of u s e r i n p u ...