The Semantic Web is a part of the current World Wide Web (WWW), which can facilitate a common mechanism to publish, share, and reuse data beyond the boundaries of web applications. It is widely believed that the majority of the datasets stored on the current web are in tabular data format (CSV, spreadsheets, SQL dumps, HTML tables etc), commonly in the comma-separated values (CSV) format. In order to prepare the CSV data semantically structured, interoperable, accessible and reusable for various web applications, they need to be extracted from the CSV files and converted into annotated table. Therefore, we propose an effective approach to generate annotated tables from CSV file. However, annotated table for CSV provides possibilities for data publishers to refer data validating, converting, displaying and inputting by following the Semantic Web standard. This research presents the conversion strategies of CSV file into annotated tables. Here, we design a parsing algorithm and development techniques to demonstrate the annotated tabular data model (column, row, and cell). An experiment is carried out to observe and compare the time efficiency of the annotation process. This method and findings provide a valuable reference for potential implementers to further operate the Semantic data.