《Table 5 The performance of the rule-based method in specific scenarios》

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《Automatic extraction and structuration of soil–environment relationship information from soil survey reports》

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To explore the impact of text types on the performance of the CRFs-based method，CRFs models of parent material were trained and validated separately by the descriptive texts of soil types and typical profiles.The validation results are shown in Tables 8 and 9.The maximum F1 value for the descriptive text of soil types was 90.7%，while the maximum F1 value for the descriptive text of soil profiles was only 75%.For the descriptive text of soil types，the optimal context window size was three and the optimal features were the combination of Wn，Pn and key value（Kn）.For the descriptive text of soil profiles，the optimal context window size was two and the optimal features were the combination of Wn and Pn.These results indicated that text type had a significant impact on the performance of the CRFs model for the parent material variable.The descriptive texts of different soil types usually have similar styles and vocabularies to describe the parent material information，which are relatively easy for the CRFs to model.In contrast，the descriptive text of different soil profiles is often written using more diverse styles and vocabularies，so they are harder to be modeled.