Document Editor Fact Validation Engine
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Solution Overview
Problem
Users face challenges in verifying the accuracy of statements entered into document editors, as existing systems lack automated validation capabilities, leaving users solely responsible for ensuring the factual correctness of their inputs.
Innovation Solution
The implementation of a validation engine utilizing natural language processing and machine learning techniques to check the correctness of statements by performing coreference resolution, entity resolution, predicate resolution, and graph traversal, with the option to provide autocorrect suggestions, and utilizing rule-based approaches for offline operations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If automated validation engine is implemented, then statement accuracy is improved, but device complexity increases
Solution Approach 1:
The patent introduces an intermediary validation engine that acts as a mediator between the user and the document editor. This engine includes specialized components (entity resolution module, predicate resolution module, coreference resolution module) that work together to validate statements automatically. The intermediary handles the complexity of validation internally while presenting a simple interface to users, thus improving statement accuracy without significantly increasing the perceived device complexity for end users.
2Reliability
If online validation engine is used, then validation capability is improved, but loss of time occurs during network dependency
Solution Approach 1:
The patent implements preliminary action by allowing the validation engine to perform validations using locally cached knowledge bases when network connectivity is unavailable. The system prepares validation data in advance and stores it locally, enabling offline validation operations. This approach maintains validation capability without network dependency and eliminates time loss associated with network requests during offline operations.
3Measurement precision
If comprehensive validation is performed, then measurement precision is improved, but productivity decreases
Solution Approach 1:
The patent applies partial action by implementing selective validation that focuses on specific statement types and contexts rather than validating every input uniformly. The validation engine analyzes the document context and applies validation selectively to statements that require fact-checking, while skipping obvious or contextually clear statements. This approach maintains high measurement precision for validated statements while improving overall productivity by reducing unnecessary validation overhead.
Data Source
AI summary
Representative embodiments disclose mechanisms to validate statements made as part of a document creation or editing process. As the user edits or creates a document using a document creation/editing application, statements made in the document can be submitted to a validation service in a proactive or reactive manner. The statement validation service receives the statement, resolves any coreferences using a coreference resolution process. Once coreferences in the statement have been resolved and replaced, entities are resolved using an entity resolution process. Predicates are then resolved using a predicate resolution process. Entity-predicate pairs are then used to traverse a knowledge graph to extract information relevant to the statement. Suggested corrections are created from the extracted information and presented to the user via the document creation/editing application.


