Named Entity Recognisers (NERs) are typically used by question answering (QA) systems as means to preselect answer candidates. However, there has not been much work on the formal assessment of the use of NERs for QA nor on their optimal parameters. In this paper we investigate the main characteristics of a NER for QA. The results show that it is important to maintain high recall to retain all possible answers on the one hand, while high precision is essential during the final answer selection phase. We present an NER designed for QA, which aims at having a high recall.8 page(s
Nowadays, one subfield of information extraction, Named Entity Recognition, becomes more and more im...
Named entity recognition (NER) is of vital importance in information extraction in natural language ...
International audienceSince the Message Understanding Conferences on Information Extraction in the 8...
Current text-based question answering (QA) systems usually contain a named entity recogniser (NER) a...
Named Entity Recognition (NER) plays a relevant role in several Natural Language Processing tasks. Q...
Question answering on speech transcripts (QAst) is a pilot track of the CLEF competition. In this pa...
Named Entity Recognition (NER) is broadly used as a first step toward the interpretation of text doc...
Named Entity Recognition (NER) and Question Answering (QA) are fundamental tasks and they are the co...
Merapi volcano museum is a place to get some information about active mountain activities, the gener...
openNamed Entity Recognition (NER) is a Natural Language Processing (NLP) task that involves detecti...
Klinger R, Friedrich CM. User's Choice of Precision and Recall in Named Entity Recognition. In: Ange...
We describe a method based on “tweaking” an existing learned sequential classifier to change the rec...
Al Quran is the guidance of all Muslims all over the world, including Indonesian society that most ...
Answering complex natural language questions with crisp answers is crucial towards satisfying the in...
The Answer Validation Exercise (AVE) 2006 is aimed at developing systems able to decide whether the ...
Nowadays, one subfield of information extraction, Named Entity Recognition, becomes more and more im...
Named entity recognition (NER) is of vital importance in information extraction in natural language ...
International audienceSince the Message Understanding Conferences on Information Extraction in the 8...
Current text-based question answering (QA) systems usually contain a named entity recogniser (NER) a...
Named Entity Recognition (NER) plays a relevant role in several Natural Language Processing tasks. Q...
Question answering on speech transcripts (QAst) is a pilot track of the CLEF competition. In this pa...
Named Entity Recognition (NER) is broadly used as a first step toward the interpretation of text doc...
Named Entity Recognition (NER) and Question Answering (QA) are fundamental tasks and they are the co...
Merapi volcano museum is a place to get some information about active mountain activities, the gener...
openNamed Entity Recognition (NER) is a Natural Language Processing (NLP) task that involves detecti...
Klinger R, Friedrich CM. User's Choice of Precision and Recall in Named Entity Recognition. In: Ange...
We describe a method based on “tweaking” an existing learned sequential classifier to change the rec...
Al Quran is the guidance of all Muslims all over the world, including Indonesian society that most ...
Answering complex natural language questions with crisp answers is crucial towards satisfying the in...
The Answer Validation Exercise (AVE) 2006 is aimed at developing systems able to decide whether the ...
Nowadays, one subfield of information extraction, Named Entity Recognition, becomes more and more im...
Named entity recognition (NER) is of vital importance in information extraction in natural language ...
International audienceSince the Message Understanding Conferences on Information Extraction in the 8...