It is difficult to extract contents of images from image data itself. To avoid this difficulty, we intend to extract the content information of images from the explanation texts of image data. We select a pictorial book of flora as the explanation texts of image data. In that text, the properties of elements in image data (plants and its part) are often expressed in copular sentences. Therefore, we intend to extract the information about the properties of plants and its parts from copular sentences. To extract these information from the pictorial book of flora, we need technical knowledge of botany, namely, the relationship among technical terms in botany and the properties of plants and its parts. This technical knowledge is usually obtained by hand because it is difficult to obtain it automatically. In this paper, we described a new method of technical knowledge acquisition for information extraction from the pictorial book of flora. Our method is as follows. We extracted these copular sentences using simple pattern matching method, established relationship among the subject words of copular sentences manually, and classified the predicates of copular sentences automatically using a character-based best matching retrieval method and a method of finding coordinate structures of a sentence. We used this technical knowledge for the analysis of modifier phrases and the semantic analysis of copular sentences in the pictorial book of flora. We obtained the correct recognition scores of 96% in the analysis of modifier phrases and 87% in the semantic analysis of copular sentences.