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Text data relationship extraction method, apparatus and device, and readable storage medium

A text data and relational extraction technology, applied in unstructured text data retrieval, text database clustering/classification, relational database, etc., can solve problems such as time-consuming, poor portability, and lack of training corpus

Pending Publication Date: 2021-03-26
BEIJING UNIV OF POSTS & TELECOMM
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  • Claims
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Problems solved by technology

[0003] At present, various methods based on relational extraction problems are mainly oriented to general fields, which makes it difficult to construct knowledge graphs in specific fields, because there is no available training corpus, and the usual method is manual labeling, but this method takes a long time. And the labor cost is expensive, and it needs to be rebuilt in different fields, and the portability is poor

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  • Text data relationship extraction method, apparatus and device, and readable storage medium
  • Text data relationship extraction method, apparatus and device, and readable storage medium
  • Text data relationship extraction method, apparatus and device, and readable storage medium

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Embodiment Construction

[0039] Hereinafter, exemplary embodiments of the present disclosure will be described in detail with reference to the accompanying drawings so that those skilled in the art can easily realize them. Also, for clarity, parts not related to describing the exemplary embodiments are omitted in the drawings.

[0040] In the present disclosure, it should be understood that terms such as "comprising" or "having" are intended to indicate the presence of features, numbers, steps, acts, components, parts or combinations thereof disclosed in the specification, and are not intended to exclude one or a plurality of other features, numbers, steps, acts, parts, parts or combinations thereof exist or are added.

[0041] In addition, it should be noted that, in the case of no conflict, the embodiments in the present disclosure and the features in the embodiments can be combined with each other. The present disclosure will be described in detail below with reference to the accompanying drawings...

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Abstract

The embodiment of the invention discloses a text data relationship extraction method, device and equipment and a readable storage medium. The method comprises the steps of obtaining text data with a keyword tag; constructing sentences according to the keyword tags and a predetermined entity relationship, and taking the sentences and text data as input data of a reading understanding model; and judging whether an answer output by the reading understanding model is a correct entity in the text data or not, and if so, marking the two entities and an entity relationship in the text data. Accordingto the technical scheme, sentences formed by keyword tags and predetermined entity relations and text data serve as input data of a reading understanding model, whether answers of the reading understanding model to the sentences are correct entities in the text data or not is judged, and if yes, the entities in the text data and the entity relations are marked; the problem of lack of training corpora in the application field of relation extraction is solved, and the cost is reduced.

Description

technical field [0001] The present disclosure relates to the technical field of natural language processing, and in particular to a method, device, device and readable storage medium for extracting relations of text data. Background technique [0002] In the field of natural language processing, relationship extraction usually refers to the connection between entities in the text, such as grammatical relationship, semantic relationship, etc., and the relationship between entities is usually described as a relational triple <E1, R, E2 >, where E1 and E2 refer to the entity type, and R refers to the relationship description type. The main purpose of entity relationship extraction is to identify and determine the specific relationship between entity pairs from natural language texts. After the text undergoes two data preprocessing processes, named entity recognition and keyword recognition, the determined triplets <E1, R , E2> stored in the database for further ana...

Claims

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Application Information

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IPC IPC(8): G06F16/36G06F16/28G06F16/35G06F40/205
CPCG06F16/367G06F16/288G06F16/35G06F40/205
Inventor 苗建松李海瑞王储
Owner BEIJING UNIV OF POSTS & TELECOMM
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