151 results about "Syntactic parsing" patented technology

A Natural Language Understanding system is provided for indexing of free text documents. The system according to the invention utilizes typographical and functional segmentation of text to identify those portions of free text that carry meaning. The system then uses words and multi-word terms and phrases identified in the free to text to identify concepts in the free text. The system uses a lexicon of terms linked to a formal ontology that is independent of a specific language to extract concepts from the free text based on the words and multi-word terms in the free text. The formal ontology contains both language independent domain knowledge concepts and language dependent linguistic concepts that govern the relationships between concepts and contain the rules about how language works. The system according to the current invention may preferably be used to index medical documents and assign codes from independent coding systems, such as, SNOMED, ICD-9 and ICD-10. The system according to the current invention may also preferably make use of syntactic parsing to improve the efficiency of the method.

A natural language understanding system is described which provides for the generation of concept codes from free-text medical data. A probabilistic model of lexical semantics, in the preferred embodiment of the invention implemented by means of a Bayesian network, is used to determine the most probable concept or meaning associated with a sentence or phrase. The inventive method and system includes the steps of checking for synonyms, checking spelling, performing syntactic parsing, transforming text to its "deep" or semantic form, and performing a semantic analysis based on a probabilistic model of lexical semantics. In the preferred embodiment of the invention, spell checking and transformational processing as well as semantic analysis make use of semantic probabilistic determinations.

A method of generating a parser of a source code file that references a syntactic dictionary, a method of compressing the file, and apparatuses that use the methods. The syntactic dictionary is converted into a corresponding plurality of expressions, of a context-free grammar, that are a grammar of the source code. The parser is constructed from the expressions. The source code is compressed using the parser. Preferably, the grammar of the source code file is a D-grammar and the expressions are regular expressions. Preferably, the parser is a deterministic pushdown transducer. An important case of the present invention is that in which the source code is XML code and the syntactic dictionary is the document type declaration of the XML code. Apparatuses that use a parser of the present invention include compressors, decompressors, validators, converters, editors, network devices and end-user / hand-held devices.

The invention provides a method and a system for converting the query sentence of a database. After a database table and a field are set, the name and field of the required database are selected in the foreground and the self-defined query sentence is inputted by a user according to the service requirement, and the query sentence inputted by the user is subjected to grammar analysis and validation, thus finishing the analysis by scanning the query sentence for only one time. By converting the service Chinese query sentence into a standard English SQL (structured query language) query sentence required by a service system, the invention fulfills the function of converting a service database query sentence into a standard executable SQL sentence, wherein the sentence acquired by the service system is directly available to the system, so that a common user can flexibly and freely use the database without mastering the query tool, SQL syntax and other professional technique of the database.

A system for extracting information from text, the system including parsing functionality operative to parse a text using a grammar, the parsing functionality including named entity recognition functionality operative to recognize named entities and recognition probabilities associated therewith and relationship extraction functionality operative to utilize the named entities and the probabilities to determine relationships between the named entities, and storage functionality operative to store outputs of the parsing functionality in a database.

The invention provides an implicit discourse relation analyzing method based on a recurrent neural network and belongs to the technical field of natural language processing application. The method comprises the following steps that firstly, word vectors of a training corpus are initialized based on a certain regulation; then, the word vectors serve as inputs of a Bi-LSTM model, two hidden-layer vectors of the Bi-LSTM model are obtained, and the two hidden-layer vectors are stitched and then serve as inputs of the recurrent neural network, wherein a syntactic parsing tree of the network structure is obtained through annotation of a PDTB corpus, and a composite function is synthesized by using neural tensors; finally, the vector representation of each argument is obtained, the two argument vectors are stitched and then input an MLP for classification, parameters in the model are updated by using a stochastic gradient descent method to be convergent, and the analysis of the implicit discourse relation is completed by using the parameters with optimal performance.

A system and method is configured to parse web-document based on elements. The system can include a word parser for extracting and separating all tokens of the document supplied to the terminal regardless of kind of a markup language used to compose the web-document by referring to a token table; and a syntax parser for parsing syntax for the tokens extracted and separated by the word parser on the basis of a contents model, and generating a object on the basis of GUI of the terminal through the parsed syntax. The token table can include tokens defined in an XML document, keywords defined in document type definition (DTD) for all documents provided to the handheld terminal, and a list of elements that can be supported by each terminal. The contents model can be determined in accordance with DTD for all documents provided to the terminal and include a hierarchy of elements and an attribute list.

The invention discloses a file serialization method of a model library of physical modeling language Modelica. The method is characterized by comprising the following steps: while loading the model library for the first time, lexical / syntactic analysis is carried out on source files of the Modelica model library; a document object model (DOM) abstract syntax tree is established; and the data of the DOM abstract syntax tree is saved in serialization destination files by a serialization technology. Meanwhile the invention further discloses a corresponding deserialization method. The method disclosed by the invention has the advantages that by means of the preprocessing course, while loading the model library for the first time, the serialization destination files are generated so as to facilitate loading the model library next time only by directly reading the destination files, thus avoiding lexical / syntactic analysis of the model library every time and greatly accelerating the loading speed of the model library. A Modelica2.1 standard library is taken as an example: while not using the method, the loading time is 300 seconds; and while using the method, the loading time is only 600 milliseconds.

A method is provided for identifying non-local relationships between licensing elements in a text segment and a word or phrase external to the text segment during a syntactic parse. Under the method, certain syntactic rules for combining words or phrases with text segments indicate that there is a possibility that the word or phrase being combined with the text segment will fill a gap in a relationship within the text segment. Based on this possibility, the text segment is searched to determine if there are any unfilled gaps in the text segment. Under some embodiments, if an unfilled gap is found, the location of the gap and the role the word or phrase plays in the gap are stored in a data structure associated with the syntactic node formed by combining the word or phrase with the text segment.

There are provided a natural language processing apparatus, a natural language processing method, and a natural language processing program which can improve the accuracy of a parsing result in syntax parsing using a pattern rule. In the natural language processing apparatus, the natural language processing method, and the natural language processing program, a pattern rule with sentence ID to which a sentence ID representing the possibility of simultaneously applying the sentence ID to the same sentence is prepared in advance. When syntax parsing of an input sentence is performed with reference to the prepared pattern rule, a large number of pattern rules to which the same sentence ID is given are included in the parsing result.

The invention provides a method for extracting an event sentence pattern from a Chinese sentence. The method comprises the following steps of: initializing by a computer, wherein the initialization of the computer comprises steps of defining relative terms, loading a data file, setting a data structure and loading a basic processing module; taking information initialized by the computer as input data; extracting the event sentence pattern according to the input information; acquiring event blocks according to the event sentence pattern; acquiring a universal role labeling result of each event block; and acquiring the role labeling result special for each event block according to the universal role labeling result. By the method of the invention, a heuristic rule can be flexibly utilized, the entire processing process can conform to the characteristics of a language per se, meanwhile the method does not need complete syntactic parsing, and the requirements on a syntactic parser are reduced, so that various conventional parsing tools can be conveniently utilized, and Chinese shallow semantic parsing is realized.

The invention relates to a method for automatically correcting syntax errors in an English composition based on multivariate features. The method comprises a syntax error correcting preprocessing module, a syntax error correcting model training module and a syntax error checking and correcting module, wherein the syntax error correcting preprocessing module carries out part-of-speech tagging of words, syntactic parsing of sentences and word frequency statistics of words for input training texts; the syntax error correcting model training module extracts words and part-of-speech context syntactic features thereof, words and part-of-speech structure-dependent syntactic features thereof and words and part-of-speech syntactic features thereof, calculates syntactic feature weight of words and outputs a statistical model of syntax error correcting for a part-of-speech tagging library of input words, a syntax tree structure library of sentences, a word frequency statistics library of words and a part-of-speech and syntax confusion set of words; and the syntax error checking and correcting module utilizes the statistical model of syntax error correcting and a rule model of syntax error correcting to correct syntax errors in a composition to be corrected and outputs the corrected results of the syntax errors in the English composition. The method can automatically correct eleven kinds of common English syntax errors in the English composition.

The invention discloses a Chinese hedge scope detection method based on a stacked neural network. The Chinese hedge scope detection method is characterized by comprising the following steps: carrying out word segmentation processing on sentences which contain hedges in a to-be-analyzed experimental corpus; carrying out syntactic parsing on the sentences after the word segmentation processing by employing a syntactic parser to obtain a phrase structure tree of the sentences; finding candidate phrases via a phrase-based candidate sample screening strategy, thereby determining boundary words of the candidate phrases, including left boundary words and right boundary words; respectively filtering the left and right boundary words as well as context information of the hedges by employing filtering windows; taking the left and right boundary words as well as the context information of the hedges as candidate sample word sequences and mapping to a real number vector space to convert into a word vector form; inputting a stacked learning model LSTM (Long Short Term Memory networks)-CNN (Convolutional Neural Network) based on a combination of the LSTM and the CNN for learning to obtain boundary classifiers; and carrying out classification on test data to obtain classification results of left and right boundaries.

The invention provides a query sentence processing device and a query sentence processing method. The query sentence processing device comprises a rule definition module 102, a syntactic analysis module 104 and a rule processing module 106, wherein the rule definition module 102 is used for setting a rule for processing self-defined elements; the syntactic analysis module 104 is used for analyzing an expression to acquire the self-defined elements in the module 104; and the rule processing module 106 is used for processing the self-defined elements according to the rule and forming query sentences by using a processing result of the elements. By a preset rule, the elements of the expression are converted into an identifiable form of the current database, so that the expression can be applied to any database.

Grammatical parsing is utilized to parse structured layouts that are modeled as grammars. This type of parsing provides an optimal parse tree for the structured layout based on a grammatical cost function associated with a global search. Machine learning techniques facilitate in discriminatively selecting features and setting parameters in the grammatical parsing process. In one instance, labeled examples are parsed and a chart is generated. The chart is then converted into a subsequent set of labeled learning examples. Classifiers are then trained utilizing conventional machine learning and the subsequent example set. The classifiers are then employed to facilitate scoring of succedent sub-parses. A global reference grammar can also be established to facilitate in completing varying tasks without requiring additional grammar learning, substantially increasing the efficiency of the structured layout analysis techniques.

Disclosed herein is an NLP system that is able to extract meaning from a natural language message using improved parsing techniques. Such an NLP system can be used in concert with an NLG system to interactively interpret messages and generate response messages in an interactive conversational stream. The parsing can include (1) named entity recognition that contextualizes the meanings of words in a message with reference to a knowledge base of named entities understood by the NLP and NLG systems, (2) syntactically parsing the message to determine a grammatical hierarchy for the named entities within the message, (3) reduction of recognized named entities into aggregations of named entities using the determined grammatical hierarchy and reduction rules to further clarify the message's meaning, and (4) mapping the reduced aggregation of named entities to an intent or meaning, wherein this intent / meaning can be used as control instructions for an NLG process.

The invention relates to the technical field of artificial intelligence, and provides a structured query language conversion method based on a natural language, and related equipment thereof. The structured query language conversion method based on the natural language comprises the following steps: obtaining a natural language text from a preset database; performing word segmentation processing on the natural language text to obtain natural language segmented words; obtaining a target text in a mode of mapping the natural language segmented words through a vocabulary analysis end; performinggrammar analysis on the target text by utilizing a preset grammar analyzer to generate an analyzed text; matching a preset select identifier and a preset where identifier with the identifier information in the analysis text respectively, and determining a select clause, a work clause and a from clause according to an obtained matching result; and generating a structured query language based on theselect clause, the where clause and the from clause. The natural language is rapidly and accurately converted into SQL, the accuracy of query by a user through the SQL is further guaranteed, and theworking efficiency of the user is improved.

Disclosed herein is an NLP system that is able to extract meaning from a natural language message using improved parsing techniques. Such an NLP system can be used in concert with an NLG system to interactively interpret messages and generate response messages in an interactive conversational stream. The parsing can include (1) named entity recognition that contextualizes the meanings of words in a message with reference to a knowledge base of named entities understood by the NLP and NLG systems, (2) syntactically parsing the message to determine a grammatical hierarchy for the named entities within the message, (3) reduction of recognized named entities into aggregations of named entities using the determined grammatical hierarchy and reduction rules to further clarify the message's meaning, and (4) mapping the reduced aggregation of named entities to an intent or meaning, wherein this intent / meaning can be used as control instructions for an NLG process.

The present disclosure relates to a syntax parsing apparatus based on syntax preprocessing and a method thereof. In specific, the present disclosure parses syntaxes that can be parsed by rules and patterns without ambiguity by syntax parsing preprocessing, draws all possible syntax parsing results by applying syntax rules based on a result of syntax parsing preprocessing in which ambiguity is partially resolved, and resolves structural ambiguity by applying a statistic syntax parsing model learned from a syntax tree attachment learning corpus so as to reduce ambiguity in rule-based syntax parsing and to resolve ambiguity by a statistics-based scheme so that parsing correctness and processing efficiency in a syntax parsing method can be enhanced.

The invention discloses a method and system for intelligently understanding a user query intention, and the method comprises the steps: inputting a query statement, and carrying out the word segmentation processing through combining with a dictionary; performing part-of-speech tagging on the word segmentation result; performing named entity recognition on the words after the part-of-speech tagging; and carrying out grammatical analysis through a named entity identification result and a set grammatical rule to obtain a user query intention. According to the method, the input query statements are analyzed layer by layer according to the wording characteristics in the loan auditing industry, the query intention of the user is deeply understood, and the query efficiency is improved on the premise that the accuracy is ensured.

The invention provides a method for extracting file information. The method includes the steps that file information is obtained in sequence in a paragraph mode, whether the paragraph contains at least one identification character is searched, if the identification character is found, the paragraph is used as the initial paragraph of an information block. At least one identification character of the file information is identified, so that needed information blocks can be quickly and accurately cut from the file information, formulas, sheets and / or pictures and other information in file content do not need to be identified, and the method further is suitable for files containing formulas and other information, and the application range of the method is widened. The method is combined with a support vector machine and shallow syntactic parsing, so that after primary identification, error results can be corrected, and identification accuracy is improved.

The invention discloses an intelligent contract code real-time debugging method based on a container. The main debugging process comprises the following steps: 1) inputting an intelligent contract code by a user; 2) the front-end system detects contract codes according to the configured rules, and feeds back the result whether the codes meet the standard or not; 3) a contract code is pulled from the Docker container, grammatical analysis is carried out, an intelligent contract is compiled, abi corresponding to the contract is acquired, and meanwhile, a compilation result and a grammatical error are fed back; 4) if the contract code is compiled successfully in the step 3), deploying the contract into a Hyperchin alliance chain; 5) if the contract code compilation in the step 3) fails, feeding back a failure result and giving a modification suggestion; and 6) if the contract is deployed successfully in the step 4), starting a debugging process of the contract code, capturing contract parameters input by the user, and returning a contract calling result. Compiling, deploying and debugging of the intelligent contract are integrated, so that the problem that debugging of the intelligentcontract code is not convenient and fast enough is solved.

The invention provides a multi-source database statement checking method and device, which can be applied to the technical field of big data, and the method comprises the following steps: performing grammatical analysis on to-be-analyzed structured query statements respectively corresponding to a plurality of databases to obtain an abstract syntax tree; determining preset rules according to the databases corresponding to the to-be-analyzed structured query statements; and performing rule analysis on the structured query statements of the abstract syntax tree node through the preset rules to obtain a statement check result. The invention can realize check of the structured query statement of the multi-source databases so as to improve accuracy and the execution efficiency of the structuredquery statements.

The invention relates to a Chinese-cranial nerve machine translation method fusing syntactic analytic trees, and belongs to the technical field of natural language processing. Machine translation of Chinese-Vietnamese and Vietnamese-Chinese can be realized. A Chinese-Vietnamese bilingual parallel corpus constructed through Internet crawling and manual translation is used as a training data set. The method aims to solve the problem of translation errors caused by insufficient training corpus in current Chinese-Yue machine translation. The method comprises the following steps: performing word segmentation, part-of-speech tagging and syntactic analysis on a source language to obtain a syntactic tree of the source language; and then vectorizing the syntactic labels and fusing the vectorized syntactic labels into a coding process of machine translation model training to train a machine translation model. An obtained model can effectively complete translation between Chinese and Vietnamese.An experiment result shows that compared with a benchmark system which does not fuse the syntactic parsing tree, the translation obtained by the method is smoother, and 0.6 BLEU values are improved.

The invention discloses a formalized verification method for network physical system requirements based on UPPAAL-SMC. The method comprises the following steps: expressing a demand model of a networkphysical system CPS in an EAST-ADL architecture model by using a probabilistic clock constraint normative language form; inputting the PrCCSL statement into a grammar parser, and parsing the PrCCSL statement to generate an abstract syntax tree AST; traversing the abstract syntax tree AST to extract key information of each relation or expression statement in the PrCCS L statement; matching a corresponding template for each relation or expression statement according to the content of the key information to generate an STA model and a query statement thereof, generating an STAs model, storing theSTAs model as an STAs file, inputting the STAs file into an integrator, integrating a system behavior model of a network physical system, and outputting a verifiable Net-STA model, the verifiable Net-STA model calling the formalized verification engine Verifyta of the UPPAAL-SMC model; and the Query generator outputs the current query verification statement to the Verify, and starts the Verify toexecute formalized verification. The method is based on PrCCS L and UPPAAL-SMC, and describes the probabilistic description of the network physical system demand, and carries out formalized verification on the demand.

The invention discloses a python code online editing method and electronic equipment. The method comprises: compiling that grammar analysis is compiled in advance through a programming language, wherein the grammar analysis is a python-based grammar structure, configuration of the grammar analysis is initialized, and a configuration file of a python-based grammar rule is obtained; Obtaining text information input by a user, and analyzing the text information according to the configuration file to obtain a corresponding analysis file; And converting the parsed file into a script language, and operating the script language. Through the method provided by the invention, a user can directly run the python code through the browser, so that a python code editor does not need to be installed in acomputer, a system patch and a dll file do not need to be installed, and the time is greatly saved. In addition, python codes are directly operated through the browser, so that the python codes are more convenient and faster, and the python codes can be greatly improved.