Abstract: A manufacturing method for low-magnetostrictive oriented silicon steel is provided, wherein the oriented silicon steel comprises a silicon steel substrate and an insulating coating on the surface of the silicon steel substrate. The manufacturing method comprises: performing single-sided laser etching on the silicon steel substrate, wherein the side of the silicon steel substrate, on which single-sided laser etching is performed, is a first surface, and the side opposite to the first surface is a second surface; determining a deflection difference between the first surface and the second surface based on the power of the laser etching, and determining a difference in the amount of the insulating coatings on the first surface and the second surface based on the deflection difference; and forming insulating coatings on the first surface and the second surface.

Abstract: A method and an apparatus for processing information are provided. The method can include: acquiring a word sequence obtained by performing word segmentation on two paragraphs in a text; inputting the word sequence into a to-be-trained natural language processing model to generate a word vector corresponding to a word in the word sequence; inputting the word vector into a preset processing layer of the to-be-trained natural language processing model; predicting whether the two paragraphs are adjacent, and a replaced word in the two paragraphs; and acquiring reference information of the two paragraphs, and training the to-be-trained natural language processing model to obtain a trained natural language processing model, based on the prediction result and the reference information.

Abstract: The present disclosure relates to the field of medical data processing based on natural language processing. Embodiments of the present disclosure disclose a method and apparatus for verifying a medical fact. The method may include: acquiring a description text of the medical fact; selecting a relevant paragraph related to the description text of the medical fact from a medical document; and inputting the description text of the medical fact and the corresponding relevant paragraph into a trained discrimination model for authenticity judgment, to obtain a verification result of the medical fact, the discrimination model being pre-trained based on a medical text paragraph pair extracted from the medical document, and being iteratively adjusted using a medical fact sample set including authenticity labeling information after the pre-training.

Abstract: The disclosure discloses a method and an apparatus for recognizing an entity word. The method includes: obtaining an entity word category and a document to be recognized; generating an entity word question based on the entity word category; segmenting the document to be recognized to generate a plurality of candidate sentences; inputting the entity word question and the plurality of candidate sentences into a question-answer model trained in advance to obtain an entity word recognizing result; and obtaining an entity word set corresponding to the entity word question based on the entity word recognizing result.

Abstract: Embodiments of the present disclosure provide a method, an apparatus and a device for generating entity relationship data, and a storage medium. The method includes: obtaining webpage source data corresponding to a target webpage; identifying at least one key value block from the webpage source data, wherein the key value block comprises at least one key value pair; identifying body values corresponding to the at least one key value block from the webpage source data; and generating entity relationship data corresponding to the target webpage according to the key value blocks and the body values corresponding to the key value blocks. With the technical solution the present disclosure, the webpage universality may be improved, labor cost may be reduced, and output quantity of the entity relationship data may be increased.

Abstract: Provided are a method, an apparatus and an electronic device for determining a knowledge sample data set, the method includes: acquiring a preset number of SPO triplet formats and source texts; acquiring, according to the SPO triplet formats, n SPO entries corresponding to the SPO triplet formats; searching, in the source texts, m first texts that match the n SPO entries, and generating a first knowledge sample data set; determining k second texts that meet the SPO triplet formats from the m first texts and generating a second knowledge sample data set; generating a target knowledge sample data set according to the first knowledge sample data set and the second knowledge sample data set. In the embodiments, the knowledge sample data set is automatically generated, the volume generation speed is fast, the cost is low, and the data size that can be produced is large, thus meeting the training requirement.

Abstract: The disclosure discloses a method and an apparatus for recognizing an entity word. The method includes: obtaining an entity word category and a document to be recognized; generating an entity word question based on the entity word category; segmenting the document to be recognized to generate a plurality of candidate sentences; inputting the entity word question and the plurality of candidate sentences into a question-answer model trained in advance to obtain an entity word recognizing result; and obtaining an entity word set corresponding to the entity word question based on the entity word recognizing result.

Abstract: A method and an apparatus for extracting SPO triples, an electronic device, and a storage medium are related to the field of artificial intelligence technologies.

Abstract: The present disclosure relates to the field of medical data processing based on natural language processing. Embodiments of the present disclosure disclose a method and apparatus for verifying a medical fact. The method may include: acquiring a description text of the medical fact; selecting a relevant paragraph related to the description text of the medical fact from a medical document; and inputting the description text of the medical fact and the corresponding relevant paragraph into a trained discrimination model for authenticity judgment, to obtain a verification result of the medical fact, the discrimination model being pre-trained based on a medical text paragraph pair extracted from the medical document, and being iteratively adjusted using a medical fact sample set including authenticity labeling information after the pre-training.

Abstract: A method and an apparatus for processing information are provided. The method can include: acquiring a word sequence obtained by performing word segmentation on two paragraphs in a text; inputting the word sequence into a to-be-trained natural language processing model to generate a word vector corresponding to a word in the word sequence; inputting the word vector into a preset processing layer of the to-be-trained natural language processing model; predicting whether the two paragraphs are adjacent, and a replaced word in the two paragraphs; and acquiring reference information of the two paragraphs, and training the to-be-trained natural language processing model to obtain a trained natural language processing model, based on the prediction result and the reference information.

Abstract: A method and apparatus for generating a temporal knowledge graph, a device and a medium. An embodiment of the method comprises: acquiring corpus including time information; performing multivariate data extraction on the corpus, multivariate data including an entity pair, an entity relationship and a target time interval of the entity relationship, the target time interval being used to indicate a valid period of the entity relationship; and generating a temporal knowledge graph based on the entity pair, the entity relationship and the target time interval of the entity relationship.

Abstract: The present disclosure provides a method, a terminal device and a storage medium for mining an entity description tag. The method includes: acquiring a group of one or more core words corresponding to each field and a first syntax dependent template corresponding to each core word; performing a matching on each data in a first data source by using the first syntax dependent template to determine a first description tag set in each field; performing a recognition on each data in a second data source to determine an entity set; determining a second description tag set based on a matching degree between each description tag in the description tag set of each field and each data in the second data source; and determining an entity description tag set based on a correlation between each entity in the entity set and each description tag in the second descriptive tag set.

Abstract: A method and device for extracting entity relation based on deep learning and a server are provided. The method includes: preprocessing a text to be mined, to obtain a sentence with entities in the text to be mined; determining an entity pair in the sentence according to the entities, wherein the entity pair includes at least two entities, and determining candidate relations between entities in the entity pair; and determining an entity relation between the entities in the entity pair from the candidate relations.

Abstract: Embodiments of the present disclosure provide a method, an apparatus and a device for generating entity relationship data, and a storage medium. The method includes: obtaining webpage source data corresponding to a target webpage; identifying at least one key value block from the webpage source data, wherein the key value block comprises at least one key value pair; identifying body values corresponding to the at least one key value block from the webpage source data; and generating entity relationship data corresponding to the target webpage according to the key value blocks and the body values corresponding to the key value blocks. With the technical solution the present disclosure, the webpage universality may be improved, labor cost may be reduced, and output quantity of the entity relationship data may be increased.

Abstract: Provided are a method, an apparatus and an electronic device for determining a knowledge sample data set, the method includes: acquiring a preset number of SPO triplet formats and source texts; acquiring, according to the SPO triplet formats, n SPO entries corresponding to the SPO triplet formats; searching, in the source texts, m first texts that match the n SPO entries, and generating a first knowledge sample data set; determining k second texts that meet the SPO triplet formats from the m first texts and generating a second knowledge sample data set; generating a target knowledge sample data set according to the first knowledge sample data set and the second knowledge sample data set. In the embodiments, the knowledge sample data set is automatically generated, the volume generation speed is fast, the cost is low, and the data size that can be produced is large, thus meeting the training requirement.

Abstract: The present disclosure provides a method, a terminal device and a storage medium for mining an entity description tag. The method includes: acquiring a group of one or more core words corresponding to each field and a first syntax dependent template corresponding to each core word; performing a matching on each data in a first data source by using the first syntax dependent template to determine a first description tag set in each field; performing a recognition on each data in a second data source to determine an entity set; determining a second description tag set based on a matching degree between each description tag in the description tag set of each field and each data in the second data source; and determining an entity description tag set based on a correlation between each entity in the entity set and each description tag in the second descriptive tag set.

Abstract: A method and device for extracting entity relation based on deep learning and a server are provided. The method includes: preprocessing a text to be mined, to obtain a sentence with entities in the text to be mined; determining an entity pair in the sentence according to the entities, wherein the entity pair includes at least two entities, and determining candidate relations between entities in the entity pair; and determining an entity relation between the entities in the entity pair from the candidate relations.

Abstract: The present invention provides a compound comprising a 5-membered heterocycle fused with a pyridazinone, wherein the compound is used as an FGFR kinase inhibitor, and a manufacturing method and application thereof. The invention specifically provides a compound as represented by formula (I). Various radicals are as defined in the specification. The compound provided by the invention effectively inhibits an activity of an FGFR kinase, and can be used to manufacture a pharmaceutical product for treating a disease related to the activity of the FGFR kinase.