10 results about "Partitive" patented technology

This application proposes a language model training method, a text generation method, and related apparatus. The method allows the language model to predict the weights of each word in the original sentence, obtaining weight values ​​for each word. Each word's weight represents the semantic importance expressed by that word in the original sentence. Then, a training sentence is input into the language model, enabling it to generate text based on the training sentence. The language model's loss is determined based on the weight values ​​of the masked portion of the original sentence and the generated text, and the model's parameters are adjusted accordingly. This setup allows the model to distinguish between different words and adaptively adjust the semantic importance of each word, rather than indiscriminately counting incorrect words. This enables the language model to truly understand semantics and improve the accuracy of prediction results.

The application discloses a machine translation software defect detection method based on combined semantics, comprising the following steps: S1, obtaining different Chinese translation sentences of the same English source sentence from different translation software; S2, using a word alignment model to correspond English words in the source sentence with segmented Chinese words in the Chinese translation sentences; S3, using a sentence compression model and a syntactic structure analysis method to obtain a main part and each additional part of the English source sentence respectively and form a sub-sentence set; S4, aligning each part of the English source sentence obtained in the step S3 with the corresponding translation part to obtain aligned translation of the main part and the additional part of the source sentence; and S5, detecting errors, including semantic similarity calculation and synonym checking.

The purpose is to obtain an inference device capable of generating an ethically appropriate sentence. The inference device according to the present disclosure includes: a mask data acquisition unit to acquire a character string which includes a masked portion; a word sequence acquisition unit to segment the character string into words and acquires a word sequence including a plurality of words; a control information acquisition unit to acquire an adjectival expression representing a nature or a state of a thing as a control word; and an inference unit to infer a likely candidate word for the masked portion from the control word and the word sequence and output the character string in which the masked portion is replaced with the likely candidate word.

Techniques are disclosed herein for using named entity recognition to resolve entity expression while transforming natural language to a meaning representation language. In one aspect, a method includes accessing natural language text, predicting, by a first machine learning model, a class label for a token in the natural language text, predicting, by a second machine-learning model, operators for a meaning representation language and a value or value span for each attribute of the operators, in response to determining that the value or value span for a particular attribute matches the class label, converting a portion of the natural language text for the value or value span into a resolved format, and outputting syntax for the meaning representation language. The syntax comprises the operators with the portion of the natural language text for the value or value span in the resolved format.

This disclosure describes techniques for generating a conversation summary. The techniques may include processing at least one statement indication of the conversation to determine at least one statement that is a candidate highlight of the conversation. The techniques may further include applying linguistic filtering rules to the candidate highlight to determine the candidate highlight is an actual highlight. The techniques may further include generating the conversation summary including providing the actual highlight as at least a portion of the conversation summary.

The invention discloses a large-model-based graduation thesis format and grammar detection system and method, and the system comprises a user interaction module which is used for user login, registration, graduation thesis file uploading and task management; the analyzing and positioning module is used for analyzing and extracting the content of the graduation thesis and positioning the position of a key part; the format detection module is used for verifying the format parameters of each key part of the graduation thesis and generating a format question list; the grammar detection module is used for integrating a large language model and generating a grammar modification suggestion list; and the result output module is used for integrating the format problem or the grammar modification suggestion list and generating a document with an annotation. According to the method, the graduation thesis is submitted by the user, then the detection type is selected, the corresponding detection program can be automatically operated, the Word document with the annotation can be generated after operation is completed, the user can download the Word document, the format detection result or the grammar modification suggestion is obtained, and the thesis modification workload of students and teachers is greatly reduced.

A knowledge base is developed by receiving language input from a source, vectorizing it, extracting an incomplete predicate set, querying another source for input regarding the missing part of the predicate set, and storing a complete predicate set.

The application provides a method and system for improving reading ability based on artificial intelligence, comprising: extracting keywords and sentence structures from input text through a natural language processing model to obtain a preliminary semantic representation, wherein the semantic representation includes entity relationships and dependency trees, thereby determining a core element set of the text; determining a quantitative indicator of understanding depth from a matching degree score of response data, wherein the quantitative indicator integrates response consistency and logical inference accuracy to obtain a depth verification result; generating dynamic adjustment prompts using a feedback generation module for the depth verification result, wherein the dynamic adjustment prompts include reinforced paths of logical connections and supplementary explanations of missing parts to obtain an optimized reader interaction sequence; updating a system thinking model through the optimized reader interaction sequence, wherein the system thinking model integrates the quantitative indicator and the adjustment prompts to obtain a mapping framework of transferred knowledge.

The goal is to obtain an inference device capable of generating an ethically acceptable sentence. The inference device according to the present disclosure comprises: a mask data retrieval unit for obtaining a string containing a masked section; a word sequence retrieval unit for segmenting the string into words and obtaining a word sequence containing a plurality of words; a control information retrieval unit for obtaining an adjectival expression representing a characteristic or condition of a thing as a control word; and an inference unit for inferring a candidate word for the masked section from the control word and the word sequence and for outputting the string in which the masked section is replaced by the candidate word.

Systems, stories, books, and methods for developing reading skills are disclosed. The stories include a plurality of words, including a plurality of sight words, a plurality of decodable words, and a plurality of non-decodable, non-sight (“NDNS”) words that are neither sight words nor decodable words. For each of at least a substantial portion of the plurality of NDNS words, the story includes a discrete pronunciation key (DPK) immediately adjacent to at least an initial appearance of each NDNS word of the at least a substantial portion of the plurality of NDNS words. The story is constructed to be a preselected reading level, and at least a portion of the plurality of words, optionally including at least a substantial portion of the NDNS words, may be selected, at least in part, based on the preselected reading level. Books and systems including one or more of the stories also are disclosed.