{'fraction_non_alphanumeric': 0.015233949945593036, 'fraction_numerical': 0.0, 'mean_word_length': 5.524822695035461, 'pattern_counts': {'":': 0, '<': 0, '<?xml version=': 0, '>': 0, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
Hybrid named entity recognition for question-answering system

Named entity recognition is important in a sophisticated information service such as Question-Answering and TextMining since most of the answer type and text mining unit depend on the named entity. Korean named entity recognition is difficult since each word of named entity has not specific features such as the capitalizing feature of English which represents named entity distinctly. In addition, since named entities are usually unknown words, the result of the morphological analyzer would make an error. Considering these problems this paper proposes hybrid named entity recognition system for Question-Answering which is constructed on people domain of encyclopedia. Finally, the experiment shows the soundness of proposed hybrid NER system which consists of determining word features, syllable based NER, pattern-rule based NER and statistical NER.