Entity relationship extraction method and device, electronic equipment and storage medium

A technology of entity relationship and entity, applied in the direction of electronic digital data processing, special data processing applications, instruments, etc., can solve problems such as difficult to solve dictionary relationship extraction, high manpower and material resources, time-consuming and labor-intensive corpus labeling, etc.

Active Publication Date: 2021-01-15
PERFECT WORLD HLDG GRP CO LTD
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  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, different fields have different expertise, therefore, the rules formulated for a certain field cannot be transplanted to other fields, which leads to the poor portability of the rule-based entity relationship extraction method; for the dictionary-based entity relationship The extraction method, because it can only identify the relationship between entities in sentences with verbs as the central word, it is difficult to realize the identification and reasoning of relational structures such as synonyms and antonyms, and it is difficult to solve the relationship ext

Method used

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  • Entity relationship extraction method and device, electronic equipment and storage medium
  • Entity relationship extraction method and device, electronic equipment and storage medium
  • Entity relationship extraction method and device, electronic equipment and storage medium

Examples

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example 1

[0130] Assuming that the target text is "Guangzhou Lixin Equity Investment Fund Management Co., Ltd. owns Libai Center, a first-tier Jiangjing Grade A office building", it is understandable that the part-of-speech tag of each word in the target text and the dependency between the word and its parent node are sequentially Combination of relationship labels, the initial syntax pattern can be obtained: Guangzhou Lixin Equity Investment Fund Management Co., Ltd.|n-SBV-owned|v-VOB-Liby Center, a first-tier Jiangjing grade-A office building|n.

example 2

[0132] Assuming that the target text is "Guangzhou Lixin Equity Investment Fund Management Co., Ltd. was established in 2018", it is understandable that the part-of-speech tag of each word in the target text is combined with the dependency label between the word and its parent node in turn, The initial syntax pattern can be obtained: Guangzhou Lixin Equity Investment Fund Management Co., Ltd.|n-SBV-established|vin|p-CMP-2018|m-POB-year|q.

example 3

[0134] Assuming that the target text is "Zhao Zhenxiang, chairman of Shenzhen Huazhi IoT Technology Co., Ltd.", it is understandable that the part-of-speech tag of each word in the target text is combined with the dependency label between the word and its parent node in turn, which can be Get the initial syntax pattern: Shenzhen|n-ATT-Huazhi Wulian|n-ATT-Technology|n-ATT-Co., Ltd.|n-ATT-Chairman|n-ATT-Zhao Zhenxiang|n.

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Abstract

The embodiment of the invention relates to an entity relationship extraction method and device, electronic equipment and a storage medium, and the method comprises the steps: carrying out word segmentation of a to-be-extracted target text to acquire words; performing part-of-speech tagging on each word to obtain a part-of-speech tag of each word; performing dependency syntax analysis on the targettext based on the part-of-speech label of each word to obtain a dependency syntax tree of the target text; and determining a syntax mode conforming to the target text based on the dependency syntax tree, and extracting an entity relationship triad from the target text based on the syntax mode. Therefore, the entity relationship triples can be efficiently and accurately extracted from the corpus data.

Description

technical field [0001] Embodiments of the present invention relate to the technical field of natural language processing, and in particular, relate to an entity relationship extraction method, device, electronic equipment, and storage medium. Background technique [0002] With the development of the Internet, a large number of different forms of Internet data are generated every day in various fields. How to accurately and efficiently mine important information in Internet data to improve service efficiency in this field is a key issue. Furthermore, in information mining, entity relationship extraction is one of the core tasks. At present, commonly used entity relationship extraction methods include rule-based entity relationship extraction methods, dictionary-based entity relationship extraction methods, and machine learning-based entity relationship extraction methods. [0003] Among them, for the rule-based entity relationship extraction method, the emphasis is on the de...

Claims

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Application Information

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IPC IPC(8): G06F40/279G06F40/211G06F16/33
CPCG06F40/279G06F40/211G06F16/3344
Inventor 任梦星刘炎覃建策陈邦忠
Owner PERFECT WORLD HLDG GRP CO LTD
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