The application belongs to the technical field of
data labeling, and discloses a method,
system, device and terminal for automatically labeling text about judgment documents, wherein the text with
punctuation symbols is divided into sentences and then input into a Jieba Chinese parser for word segmentation; based on the word frequency word segmentation result, a
dynamic programming method is used to find the path with the maximum probability, and the text word segmentation terms are stored in an intermediate
database; the manually labeled text is trained through a
machine learning model, and automatic labeling of the text is realized through a constructed corpus labeling
library; after the
annotation data in the
database are scored, the labeling is automatically reloaded, and
data sorting is performed according to the labeling
score. Through the method combining
text enhancement and semi-
supervised learning, the target case document is subjected to event extraction and labeling according to preset event extraction rules, and combined with an external
online database, the labor cost of text entity labeling is greatly reduced, and the efficiency and accuracy of text labeling are improved.