In this paper we investigate the use of linguistic knowledge in passage retrieval as part of an open-domain question answering system. We use annotation produced by a deep syntactic dependency parser for Dutch, Alpino, to extract various kinds of ...

We consider the problem of question-focused sentence retrieval from complex news articles describing multi-event stories published over time. Annotators generated a list of questions central to understanding each story in our corpus. Because of the ...

In this work we propose a translation model for monolingual sentence retrieval. We propose four methods for constructing a parallel corpus. Of the four methods proposed, a lexicon learned from a bilingual Arabic-English corpus aligned at the sentence ...

A reading comprehension (RC) system attempts to understand a document and returns an answer sentence when posed with a question. RC resembles the ad hoc question answering (QA) task that aims to extract an answer from a collection of documents when ...

Traditional question answering systems adopt the following framework: parsing questions, searching for relevant documents, and identifying/generating answers. However, this framework does not work well for questions with hidden assumptions and ...

Numerous NLP applications rely on search-engine queries, both to extract information from and to compute statistics over the Web corpus. But search engines often limit the number of available queries. As a result, query-intensive NLP applications such ...

We have studied how context specific web corpus can be automatically created and mined for discovering semantic similarity relationships between terms (words or phrases) from a given collection of documents (target collection). These relationships ...

Key phrases are usually among the most information-bearing linguistic structures. Translating them correctly will improve many natural language processing applications. We propose a new framework to mine key phrase translations from web corpora. We ...

We present a practically unsupervised learning method to produce single-snippet answers to definition questions in question answering systems that supplement Web search engines. The method exploits on-line encyclopedias and dictionaries to generate ...

We approached the problem as learning how to order documents by estimated relevance with respect to a user query. Our support vector machines based classifier learns from the relevance judgments available with the standard test collections and ...

We propose an approach to summarization exploiting both lexical information and the output of an automatic anaphoric resolver, and using Singular Value Decomposition (SVD) to identify the main terms. We demonstrate that adding anaphoric information ...