Semantic Role Labeling (SRL) has been used successfully in several stages of automated Question Answering (QA) systems but its inherent slow procedures make it difficult to use at the indexing stage of the document retrieval component. In this paper we confirm the intuition that SRL at indexing stage improves the performance of QA and propose a simplified technique named the Question Prediction Language Model (QPLM), which provides similar information with a much lower cost. The methods were tested on four different QA systems and the results suggest that QPLM can be used as a good compromise between speed and accuracy.8 page(s
This paper presents our experiments with a low-frequency approach to information retrieval for quest...
This article provides a comprehensive and comparative overview of question answering technology. It ...
AbstractThe need to query information content available in various formats including structured and ...
This paper introduces the task of question-answer driven semantic role labeling (QA-SRL), where ques...
In this demo, we will present QASR- a question answering system that uses semantic role labeling. Gi...
Question answering (QA) aims at retrieving precise information from a large collection of documents....
Retrieval augmented language models have recently become the standard for knowledge intensive tasks....
This paper introduces the technique of Predictive Annotation, a methodology for indexing texts for r...
Within a Question Answering (QA) framework, Question Context plays a vital role. We define Question ...
Within a Question Answering (QA) framework, Question Context plays a vital role. We define Question ...
In this article, we present a factoid question-answering system, Sibyl, specifically tailored for qu...
Open Domain Question Answering (ODQA) aims at automatically understanding and giving responses to ge...
International audienceThe Semantic Web contains an enormous amount of information in the form of kno...
Automated answering of natural language questions is an interesting and useful problem to solve. Que...
We investigate the problem of passage retrieval for Question Answering (QA) systems. We adopt a mach...
This paper presents our experiments with a low-frequency approach to information retrieval for quest...
This article provides a comprehensive and comparative overview of question answering technology. It ...
AbstractThe need to query information content available in various formats including structured and ...
This paper introduces the task of question-answer driven semantic role labeling (QA-SRL), where ques...
In this demo, we will present QASR- a question answering system that uses semantic role labeling. Gi...
Question answering (QA) aims at retrieving precise information from a large collection of documents....
Retrieval augmented language models have recently become the standard for knowledge intensive tasks....
This paper introduces the technique of Predictive Annotation, a methodology for indexing texts for r...
Within a Question Answering (QA) framework, Question Context plays a vital role. We define Question ...
Within a Question Answering (QA) framework, Question Context plays a vital role. We define Question ...
In this article, we present a factoid question-answering system, Sibyl, specifically tailored for qu...
Open Domain Question Answering (ODQA) aims at automatically understanding and giving responses to ge...
International audienceThe Semantic Web contains an enormous amount of information in the form of kno...
Automated answering of natural language questions is an interesting and useful problem to solve. Que...
We investigate the problem of passage retrieval for Question Answering (QA) systems. We adopt a mach...
This paper presents our experiments with a low-frequency approach to information retrieval for quest...
This article provides a comprehensive and comparative overview of question answering technology. It ...
AbstractThe need to query information content available in various formats including structured and ...