17425556. METHOD AND APPARATUS FOR INFORMATION EXTRACTION, ELECTRONIC DEVICE, AND STORAGE MEDIUM simplified abstract (BOE TECHNOLOGY GROUP CO., LTD.)

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METHOD AND APPARATUS FOR INFORMATION EXTRACTION, ELECTRONIC DEVICE, AND STORAGE MEDIUM

Organization Name

BOE TECHNOLOGY GROUP CO., LTD.

Inventor(s)

Bingqian Wang of Beijing (CN)

METHOD AND APPARATUS FOR INFORMATION EXTRACTION, ELECTRONIC DEVICE, AND STORAGE MEDIUM - A simplified explanation of the abstract

This abstract first appeared for US patent application 17425556 titled 'METHOD AND APPARATUS FOR INFORMATION EXTRACTION, ELECTRONIC DEVICE, AND STORAGE MEDIUM

Simplified Explanation

The present disclosure describes a method and apparatus for information extraction, as well as an electronic device and a storage medium. The method involves obtaining text data and inputting it into a pre-trained information extraction model to extract triple information from the text data. The triple information consists of a subject, a predicate, and an object present in the text data. The information extraction model includes a binary classification sub-model to extract the subject and a multi-label classification sub-model to extract the predicate and object associated with the subject.

  • The method involves obtaining text data and extracting triple information from it.
  • The triple information includes a subject, predicate, and object present in the text data.
  • The information extraction model consists of a binary classification sub-model and a multi-label classification sub-model.
  • The binary classification sub-model extracts the subject from the text data.
  • The multi-label classification sub-model extracts the predicate and object corresponding to the subject based on the subject and text data.

Potential Applications

  • Natural language processing: This technology can be used in various applications that require extracting structured information from unstructured text data, such as chatbots, virtual assistants, and information retrieval systems.
  • Data analysis: The extracted triple information can be used for data analysis and knowledge discovery, enabling better decision-making and insights in fields like business intelligence, market research, and scientific research.

Problems Solved

  • Information extraction: The method solves the problem of extracting structured information from unstructured text data, which is often a challenging task due to the complexity and variability of natural language.
  • Subject-predicate-object extraction: The method specifically addresses the extraction of triple information consisting of a subject, predicate, and object, which is a common structure in many types of textual information.

Benefits

  • Accuracy: The pre-trained information extraction model improves the accuracy of extracting triple information from text data, reducing errors and improving the quality of extracted information.
  • Efficiency: The method provides an efficient way to extract triple information by utilizing a binary classification sub-model and a multi-label classification sub-model, optimizing the extraction process.
  • Versatility: The technology can be applied to various domains and industries, allowing for the extraction of triple information from different types of text data.


Original Abstract Submitted

The present disclosure provides a method and an apparatus for information extraction, an electronic device, and a storage medium. The method for information extraction includes: first obtaining text data, and then inputting the text data into an information extraction model obtained through pre-training to obtain triple information contained in the text data, wherein the triple information includes a subject, a predicate and an object in the text data. The information extraction model includes a binary classification sub-model and a multi-label classification sub-model, wherein the binary classification sub-model is configured to extract the subject in the text data, and the multi-label classification sub-model is configured to extract the predicate and the object corresponding to the subject in the text data according to the subject and the text data.

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