Methods and systems for extracting information from text
Topics: AI Mode, Brand Context, Data Mining, Entity based search, Knowledge Graph, LLM Readability, LLMO / GEO
This Google patent describes methods and systems for extracting structured information from unstructured text. The core idea involves parsing text into a tree-like structure based on the grammatical roles of words (parts of speech), then identifying paths within that tree that connect entities (such as people or places) to values (such as schools or capitals) through specific attributes (such as “alma mater” or “country capital”). Once these tree paths are discovered using known example facts, they can be reused to automatically extract new, previously unknown facts from the same or different text sources. The patent also covers validation techniques to ensure that extracted paths and facts are accurate and reliable.
Your advantages:
+ Get access to the full exclusive paid articles in the blog.
+ Full analysis of hundreds of well researched active Microsoft, OpenAI and Google patents and research paper.
+ Save a lot of time and get insights in just a few minutes, without having to spend hours analyzing the documents.
+ Get quick exclusive insights about how search engines and Google could work with easy to understand summaries and analysis.
+ All patents classified by topic for targeted research.
+ New patent summaries and analysis every week. Weekly notification via E-Mail
+ Get GEO expert knowledge for optimizing your visibility in AI Search via the LLMO / GEO assistant
+ Use all AI Research Tools to gain insights in seconds from all documents in the patent database, Google Leaks and DOJ trials via the Patent & Paper Analyzer and Google Leak Analyzer
+ Gain fundamental insights for your SEO work and become a real thought leader.
Get access to the SEO Research Suite and become a SEO thought leader now!
