Named Entity Annotation Corpus for Commercial Opportunity Mining

With the rising number of enterprises in China, enterprise data present explosive growth. Mining valuable commercial opportunity information from massive enterprise data is called commercial opportunity mining. Commercial opportunity information has rich investment reference value, it can help enterprises and investors to make better decisions, so it has important research significance. In order to solve the problem of the lack of Chinese named entity annotation corpus suitable for commercial opportunity mining research, this paper constructs the Commercial Opportunity Information named entity annotation Corpus (COIC). Based on the demand of commercial opportunity mining, we collect six types of commercial information. By deeply analyzing the characteristics of commercial texts, we define nine categories of commercial entities, and formulate the entity annotation specification. We use entity annotation platform to conduct pre-annotation, manual annotation, and manual proofreading of entities in commercial texts with more than 720,000 characters. The COIC we constructed contains 36,787 entities, and the annotation consistency reaches 0.8613. The current mainstream algorithms in the field of named entity recognition are selected for preliminary experiments, and various entities in the corpus are evaluated, which lays the data foundation for the follow-up research on commercial opportunity mining.