Metric-Type Identification

Metric-Type Identification is a crucial task in natural language processing aimed at automatically recognizing and categorizing various types of metrics that appear in text. This task involves analyzing numbers and units within the text to extract specific measurement information and classify it into predefined categories, such as length, weight, time, etc. Its goal is to enhance the structuring of textual data, thereby improving the accuracy and efficiency of information retrieval and data analysis. In fields such as scientific research, data analysis, and financial reporting, the application value of Metric-Type Identification is significant, effectively supporting the understanding and processing of complex texts.