Structured model training method, text structuring method and related devices
The embodiment of the invention provides a text structuring method. The method comprises the steps that a target text to be structured is acquired; Inputting the target text into an entity extractionmodel, and identifying a target entity set in the target text through the entity extraction model; In...
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creator | WANG ZHIQIANG LI JINGYI GUO YONGHONG HE JIA YANG GUANMEI LIU QIANNAN CHEN WEIRAN JIANG TINGXIN WANG XIZHEN DUAN BOCHAO |
description | The embodiment of the invention provides a text structuring method. The method comprises the steps that a target text to be structured is acquired; Inputting the target text into an entity extractionmodel, and identifying a target entity set in the target text through the entity extraction model; Inputting the identified target text of the target entity set into a relation extraction model, and extracting a relation between the target entities through the relation extraction model; And according to the target entities in the target entity set and the relationship between the target entities,performing structured representation on the target text to generate a target structure. In the embodiment of the invention, the conversion speed is high, and the labor cost is saved.
本申请实施例提供了种文本结构化的方法,该方法包括:获取待结构化的目标文本;将所述目标文本输入到实体提取模型,通过所述实体提取模型识别所述目标文本中的目标实体集合;将已识别到所述目标实体集合的目标文本输入到关系提取模型,通过所述关系提取模型提取所述目标实体之间的关系;根据目标实体集合中的目标实体及所述目标实体之间的关系,对所述目标文本进行结构化表示,生成目标结构。本申请实施例中,转换速度快,节省人工成本。 |
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本申请实施例提供了种文本结构化的方法,该方法包括:获取待结构化的目标文本;将所述目标文本输入到实体提取模型,通过所述实体提取模型识别所述目标文本中的目标实体集合;将已识别到所述目标实体集合的目标文本输入到关系提取模型,通过所述关系提取模型提取所述目标实体之间的关系;根据目标实体集合中的目标实体及所述目标实体之间的关系,对所述目标文本进行结构化表示,生成目标结构。本申请实施例中,转换速度快,节省人工成本。</description><language>chi ; eng</language><subject>CALCULATING ; COMPUTING ; COUNTING ; ELECTRIC DIGITAL DATA PROCESSING ; PHYSICS</subject><creationdate>2019</creationdate><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://worldwide.espacenet.com/publicationDetails/biblio?FT=D&date=20190405&DB=EPODOC&CC=CN&NR=109582800A$$EHTML$$P50$$Gepo$$Hfree_for_read</linktohtml><link.rule.ids>230,308,780,885,25564,76547</link.rule.ids><linktorsrc>$$Uhttps://worldwide.espacenet.com/publicationDetails/biblio?FT=D&date=20190405&DB=EPODOC&CC=CN&NR=109582800A$$EView_record_in_European_Patent_Office$$FView_record_in_$$GEuropean_Patent_Office$$Hfree_for_read</linktorsrc></links><search><creatorcontrib>WANG ZHIQIANG</creatorcontrib><creatorcontrib>LI JINGYI</creatorcontrib><creatorcontrib>GUO YONGHONG</creatorcontrib><creatorcontrib>HE JIA</creatorcontrib><creatorcontrib>YANG GUANMEI</creatorcontrib><creatorcontrib>LIU QIANNAN</creatorcontrib><creatorcontrib>CHEN WEIRAN</creatorcontrib><creatorcontrib>JIANG TINGXIN</creatorcontrib><creatorcontrib>WANG XIZHEN</creatorcontrib><creatorcontrib>DUAN BOCHAO</creatorcontrib><title>Structured model training method, text structuring method and related devices</title><description>The embodiment of the invention provides a text structuring method. The method comprises the steps that a target text to be structured is acquired; Inputting the target text into an entity extractionmodel, and identifying a target entity set in the target text through the entity extraction model; Inputting the identified target text of the target entity set into a relation extraction model, and extracting a relation between the target entities through the relation extraction model; And according to the target entities in the target entity set and the relationship between the target entities,performing structured representation on the target text to generate a target structure. In the embodiment of the invention, the conversion speed is high, and the labor cost is saved.
本申请实施例提供了种文本结构化的方法,该方法包括:获取待结构化的目标文本;将所述目标文本输入到实体提取模型,通过所述实体提取模型识别所述目标文本中的目标实体集合;将已识别到所述目标实体集合的目标文本输入到关系提取模型,通过所述关系提取模型提取所述目标实体之间的关系;根据目标实体集合中的目标实体及所述目标实体之间的关系,对所述目标文本进行结构化表示,生成目标结构。本申请实施例中,转换速度快,节省人工成本。</description><subject>CALCULATING</subject><subject>COMPUTING</subject><subject>COUNTING</subject><subject>ELECTRIC DIGITAL DATA PROCESSING</subject><subject>PHYSICS</subject><fulltext>true</fulltext><rsrctype>patent</rsrctype><creationdate>2019</creationdate><recordtype>patent</recordtype><sourceid>EVB</sourceid><recordid>eNrjZPANLikqTS4pLUpNUcjNT0nNUSgpSszMy8xLV8hNLcnIT9FRKEmtKFEohipDSCgk5qUoFKXmJJYAtaaklmUmpxbzMLCmJeYUp_JCaW4GRTfXEGcP3dSC_PjU4oLE5NS81JJ4Zz9DA0tTCyMLAwNHY2LUAAAh7zas</recordid><startdate>20190405</startdate><enddate>20190405</enddate><creator>WANG ZHIQIANG</creator><creator>LI JINGYI</creator><creator>GUO YONGHONG</creator><creator>HE JIA</creator><creator>YANG GUANMEI</creator><creator>LIU QIANNAN</creator><creator>CHEN WEIRAN</creator><creator>JIANG TINGXIN</creator><creator>WANG XIZHEN</creator><creator>DUAN BOCHAO</creator><scope>EVB</scope></search><sort><creationdate>20190405</creationdate><title>Structured model training method, text structuring method and related devices</title><author>WANG ZHIQIANG ; LI JINGYI ; GUO YONGHONG ; HE JIA ; YANG GUANMEI ; LIU QIANNAN ; CHEN WEIRAN ; JIANG TINGXIN ; WANG XIZHEN ; DUAN BOCHAO</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-epo_espacenet_CN109582800A3</frbrgroupid><rsrctype>patents</rsrctype><prefilter>patents</prefilter><language>chi ; eng</language><creationdate>2019</creationdate><topic>CALCULATING</topic><topic>COMPUTING</topic><topic>COUNTING</topic><topic>ELECTRIC DIGITAL DATA PROCESSING</topic><topic>PHYSICS</topic><toplevel>online_resources</toplevel><creatorcontrib>WANG ZHIQIANG</creatorcontrib><creatorcontrib>LI JINGYI</creatorcontrib><creatorcontrib>GUO YONGHONG</creatorcontrib><creatorcontrib>HE JIA</creatorcontrib><creatorcontrib>YANG GUANMEI</creatorcontrib><creatorcontrib>LIU QIANNAN</creatorcontrib><creatorcontrib>CHEN WEIRAN</creatorcontrib><creatorcontrib>JIANG TINGXIN</creatorcontrib><creatorcontrib>WANG XIZHEN</creatorcontrib><creatorcontrib>DUAN BOCHAO</creatorcontrib><collection>esp@cenet</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>WANG ZHIQIANG</au><au>LI JINGYI</au><au>GUO YONGHONG</au><au>HE JIA</au><au>YANG GUANMEI</au><au>LIU QIANNAN</au><au>CHEN WEIRAN</au><au>JIANG TINGXIN</au><au>WANG XIZHEN</au><au>DUAN BOCHAO</au><format>patent</format><genre>patent</genre><ristype>GEN</ristype><title>Structured model training method, text structuring method and related devices</title><date>2019-04-05</date><risdate>2019</risdate><abstract>The embodiment of the invention provides a text structuring method. The method comprises the steps that a target text to be structured is acquired; Inputting the target text into an entity extractionmodel, and identifying a target entity set in the target text through the entity extraction model; Inputting the identified target text of the target entity set into a relation extraction model, and extracting a relation between the target entities through the relation extraction model; And according to the target entities in the target entity set and the relationship between the target entities,performing structured representation on the target text to generate a target structure. In the embodiment of the invention, the conversion speed is high, and the labor cost is saved.
本申请实施例提供了种文本结构化的方法,该方法包括:获取待结构化的目标文本;将所述目标文本输入到实体提取模型,通过所述实体提取模型识别所述目标文本中的目标实体集合;将已识别到所述目标实体集合的目标文本输入到关系提取模型,通过所述关系提取模型提取所述目标实体之间的关系;根据目标实体集合中的目标实体及所述目标实体之间的关系,对所述目标文本进行结构化表示,生成目标结构。本申请实施例中,转换速度快,节省人工成本。</abstract><oa>free_for_read</oa></addata></record> |
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subjects | CALCULATING COMPUTING COUNTING ELECTRIC DIGITAL DATA PROCESSING PHYSICS |
title | Structured model training method, text structuring method and related devices |
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