Abstract: A text partitioning method, a text classifying method, an apparatus, a device and a storage medium, wherein the method includes: parsing a content image, to obtain a target text in a text format; according to a line break in the target text, partitioning the target text into a plurality of text sections; and according to a first data-volume threshold, partitioning sequentially the plurality of text sections into a plurality of text-to-be-predicted sets, wherein a data volume of a last one text section in each of the text-to-be-predicted sets is greater than a second data-volume threshold.

Abstract: A data labeling method and device and a computer-readable storage medium. The method includes: based on a knowledge graph, remotely acquiring data to be labeled; performing data cleaning and pre-labeling to the data to be labeled, to obtain pre-labeled data; and performing labeling correction to the pre-labeled data.

Abstract: 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.

Abstract: The disclosure provides an entity linking method and apparatus, and relates to the technical field of computers. The entity linking method comprises: recognizing a to-be-disambiguated entity in a target text; encoding the to-be-disambiguated entity to obtain a text code; encoding candidate entities corresponding to the to-be-disambiguated entity to obtain entity description codes; determining co-occurrence features between the target text and entity description information of the candidate entities; and determining an entity object corresponding to the to-be-disambiguated entity according to the text code, the entity description codes and the co-occurrence features.

Abstract: The disclosure provides an entity linking method and apparatus, and relates to the technical field of computers. The entity linking method comprises: recognizing a to-be-disambiguated entity in a target text; encoding the to-be-disambiguated entity to obtain a text code; encoding candidate entities corresponding to the to-be-disambiguated entity to obtain entity description codes; determining co-occurrence features between the target text and entity description information of the candidate entities; and determining an entity object corresponding to the to-be-disambiguated entity according to the text code, the entity description codes and the co-occurrence features.

Abstract: The present disclosure relates to the field of natural language processing technologies, and more particularly, to a method and an apparatus for information acquisition, an electronic device, and a computer-readable storage medium. The method includes: recognizing at least one entity retrieval word in a to-be-answered question; performing information retrieval according to the at least one entity retrieval word to obtain a retrieval text in a sub-graph form corresponding to the at least one entity retrieval word; determining a retrieval text in a target sub-graph form by matching the retrieval text in the sub-graph form with the to-be-answered question; and determining a target answer to the to-be-answered question according to the retrieval text in the target sub-graph form.

Abstract: 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.

Abstract: Disclosed in the present disclosure is a method for preparing 16alpha-hydroxyprednisolone, belonging to the technical field of medicine preparation and processing. In the method, 21-hydroxypregna-1,4,9(11),16-tetraene-3,20-dione-21-acetate is used as a starting material, and subjected to oxidation, bromo-hydroxylation, debromination and alcoholysis, so as to prepare 16alpha-hydroxyprednisolone. The method for preparing 16alpha-hydroxylprednisolone of the present disclosure can effectively control the generation of impurities in the reaction process by improving the disadvantages of traditional processes, and has a mild reaction process and a high overall conversion rate; and the method of the present disclosure has low requirements for a reaction device and low operation costs, is easy to operate, is suitable for industrial production, and has a good market prospect.

Abstract: The present disclosure provides a purification method of progesterone. In this method, aldehyde impurities in a progesterone crude product react with a sulfurated nucleophile to yield highly polar hydroxysulfonates and progesterone to realize solubility differentiation, and highly pure progesterone with a content higher than 99.5% and a total aldehyde impurities content lower than 0.2% is obtained through elutriation, filtration, washing a filter cake with water, and drying.

Abstract: The embodiment of the present disclosure provides a question-and-answer processing method, including: acquiring a to-be-answered question; determining standard questions meeting a preset condition as a plurality of candidate standard questions, from a plurality of preset standard questions, according to a text similarity with the to-be-answered question, based on a text statistical algorithm; determining, a candidate standard question with the highest semantic similarity with the to-be-answered question as a matching standard question, from the plurality of candidate standard questions, based on a deep text matching algorithm; and determining an answer to the to-be-answered question at least according to the matching standard question. The embodiment of the present disclosure also provides an electronic device and a computer readable medium.

Abstract: Disclosed in the present disclosure is a method for preparing 16alpha-hydroxyprednisolone, belonging to the technical field of medicine preparation and processing. In the method, 21-hydroxypregna-1,4,9(11),16-tetraene-3,20-dione-21-acetate is used as a starting material, and subjected to oxidation, bromo-hydroxylation, debromination and alcoholysis, so as to prepare 16alpha-hydroxyprednisolone. The method for preparing 16alpha-hydroxylprednisolone of the present disclosure can effectively control the generation of impurities in the reaction process by improving the disadvantages of traditional processes, and has a mild reaction process and a high overall conversion rate; and the method of the present disclosure has low requirements for a reaction device and low operation costs, is easy to operate, is suitable for industrial production, and has a good market prospect.

Abstract: A text extraction method and device, computer-readable storage medium, and electronic device are described that relate to the technical field of machine learning. The method includes: acquiring to-be-extracted data and extracting a current trigger word in the to-be-extracted data using a target trigger word extraction model included in a target event extraction model; generating a current query sentence according to the current trigger word; and extracting a current event argument corresponding to the current trigger word according to the current query sentence and a target argument extraction model included in the target event extraction model, wherein the target trigger word extraction model and the target argument extraction model have a same model structure and parameter, and are connected in a cascading manner.

Abstract: The present disclosure provides an image acquisition method, image acquisition device, electronic device, and computer-readable storage medium. The method includes: acquiring an image retrieval text input by a user and a screen display status of an image display device; determining retrieval intention information and a retrieval keyword according to the image retrieval text, wherein the retrieval intention information comprises information reflecting the user's retrieval intention, and the retrieval keyword comprises a keyword used to retrieve images; acquiring at least one candidate image according to the retrieval intention information and the retrieval keyword; and selecting a target image from the at least one candidate image according to the screen display status.

Abstract: Disclosed are an automatic question answering method and apparatus, a storage medium, and a server. The method includes: acquiring numerical features of a sentence to be queried; querying a target sentence in a question database according to the numerical features of the sentence to be queried, the question database including a plurality of sentences and answers corresponding to the plurality of sentences; and determining a target answer according to an answer corresponding to the target sentence. In this method, the sentence is represented by the numerical features, such that it is convenient to search questions similar to a question of a user in the question database, thereby achieving an effect of improving a search speed of the question.

Abstract: A method for event extraction according to the disclosure includes: processing an object text using a preset extraction model to determine event information of the object text; wherein the event information includes an event element, and an event type and a role corresponding to the event element; and the extraction model includes a classification layer and an output layer; the classification layer is configured to determine a token attribute of a token in the object text; the token attribute includes whether the token is a start token of the event element of any event type and any role, and whether the token is an end token of the event element of any event type and any role; and the output layer is configured to determine the event element according to the token attribute of the token, and determine the event type and the role corresponding to the event element.

Abstract: The application discloses an event extraction method, apparatus, device and storage medium, the method including acquiring a text to be processed, inputting the text to be processed into an event detection model to determine an event type involved in the text to be processed, constructing a first query corpus based on the event type, inputting the text to be processed and the first query corpus into a reading comprehension model to determine an event body corresponding to the event type and event elements corresponding to the event body, obtaining an event extraction result of the text to be processed based on the event body and the event elements. This method accurately determines the event type and the event elements in the text to be processed, is and is adapted to event extraction in a document level text, improving the overall performance of event extraction and promoting the efficiency of event extraction.

Abstract: A text partitioning method, a text classifying method, an apparatus, a device and a storage medium, wherein the method includes: parsing a content image, to obtain a target text in a text format; according to a line break in the target text, partitioning the target text into a plurality of text sections; and according to a first data-volume threshold, partitioning sequentially the plurality of text sections into a plurality of text-to-be-predicted sets, wherein a data volume of a last one text section in each of the text-to-be-predicted sets is greater than a second data-volume threshold.

Abstract: A data labeling method and device and a computer-readable storage medium. The method includes: based on a knowledge graph, remotely acquiring data to be labeled; performing data cleaning and pre-labeling to the data to be labeled, to obtain pre-labeled data; and performing labeling correction to the pre-labeled data.

Abstract: The present disclosure provides an image acquisition method, image acquisition device, electronic device, and computer-readable storage medium. The method includes: acquiring an image retrieval text input by a user and a screen display status of an image display device; determining retrieval intention information and a retrieval keyword according to the image retrieval text, wherein the retrieval intention information comprises information reflecting the user's retrieval intention, and the retrieval keyword comprises a keyword used to retrieve images; acquiring at least one candidate image according to the retrieval intention information and the retrieval keyword; and selecting a target image from the at least one candidate image according to the screen display status.

Abstract: Disclosed are an automatic question answering method and apparatus, a storage medium, and a server. The method includes: acquiring numerical features of a sentence to be queried; querying a target sentence in a question database according to the numerical features of the sentence to be queried, the question database including a plurality of sentences and answers corresponding to the plurality of sentences; and determining a target answer according to an answer corresponding to the target sentence. In this method, the sentence is represented by the numerical features, such that it is convenient to search questions similar to a question of a user in the question database, thereby achieving an effect of improving a search speed of the question.