{'fraction_non_alphanumeric': 0.014807502467917079, 'fraction_numerical': 0.0, 'mean_word_length': 5.3375, '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}}
Food safety Knowledge Graph and Question Answering System

The issue of food safety in recent years has always been the focus of public opinion. Every time there are unqualified foods, it will cause widespread panic and rumor spread, which has a great impact on social stability. Therefore, this paper crawled the data of unqualified foods officially released in recent years from the network, and designed the extraction algorithm of food general entities, food domain entities and relationships between entities for these data. The extracted entity pairs were stored in the gStore database. In order to solve the problem of association of knowledge in knowledge graph, this paper also designed the food safety ontology which organized the concepts, classifications and relationships about food production and food inspection. Finally, this paper also built an intelligent question answering system by means of gStore's http service to help person grasp the unqualified food information through natural language.