4results about "Semi-structured data querying" patented technology

The application discloses a long-text-oriented episodic screenplay generation method and system, and belongs to the technical field of artificial intelligence content generation and digital video production. The method forms multiple episode objects through voice-over role initialization, text semantic compression and episode segmentation, and extracts role candidate objects and location time sequence candidate objects; based on normalization rules, an identity register of roles and a location time sequence register are constructed respectively, and unified identification reuse or new registration is performed on the candidate objects; under the constraint of the register, scene planning results and structured screenplay constraint patterns are generated, and multiple generation agents are called to output screenplay objects; and then, through structure verification, field completion and unified field transformation, the standardized results of episodes, roles, locations and screenplays are output. The application can improve the consistency of cross-episode roles and locations, the stability of the screenplay structure and the reuse efficiency of downstream production.

Systems and methods for data management via a data management system are provided. The data management system can receive data relating to one or more assets, the data in one or more formats, convert the asset data to a uniform format, extract data elements, compare and normalize the data elements against a standard reference database, and automatically validate the one or more data elements. The validation can be performed by comparing data elements to requirements set by the data management system or other party, and confirming that the data elements match the requirements. The validation can operate to initiate an asset transaction.

The machine analyzes entity-resolved data graphs using a curated set of peer-reviewed data structures. [Solution] The machine uses independent peer data structures that model similar or related but different universes and entities. These data structures may include other entity-resolved data graphs or file-based data structures. The machine first performs candidate screening to determine which of these data structures meets the requirements for use in the analysis. The machine then selects from the candidate peer data structures by which it will perform the analysis. Finally, the entity-resolved data graph is analyzed using queries against the selected peer data structure to provide an analysis of the quality of that data graph.

The application provides a building construction scheme intelligent auditing method based on a rule engine and a large model, and belongs to the technical field of construction scheme intelligent auditing. The method performs Open XML structured analysis on a construction scheme document, constructs a chapter tree and divides the chapter tree into content blocks with paths; content auditing integrates structured retrieval and vector semantic retrieval, automatically extracts an engineering geographic area for regional elimination items, dynamically filters a suitable elimination item database for semantic comparison; style auditing adopts a three-level backtracking mechanism of character level, paragraph level and document default style to obtain actual effective styles, and combines a tolerance threshold and semantic font matching for accurate verification; and the auditing result is automatically inserted based on an XML offset position <w:comment>The method can effectively break through the identification bottleneck of style inheritance deviation, realize dynamic adaptation of regional specifications, and improve the depth, accuracy and automation level of the review.< / w:comment>