Semantic processor for recognition of cause-effect relations in natural language documents

This invention describes a computer program that finds cause-and-effect relationships within written documents. It works by breaking down sentences into specific subject-action-object units and then grouping these units into larger semantic chunks to identify what causes what. The program builds a knowledge base of these identified relationships.

Why it matters: Filed before the widespread adoption of deep learning and large language models (LLMs). Modern NLP techniques could significantly enhance the accuracy and scalability of cause-effect relation extraction, potentially making the pattern-based linguistic models described in 2005 obsolete or much easier to implement.

Status: Not in forceListed as no longer active. The specific reason is not in the record we hold.
How hard to build: SpecializedHeavy software system, complex NLP algorithms

3 AI reinvention directions for this patent

See all three

AI gives you a few directions you could take this. Pick one, and we check whether your version is different enough to patent, then write the filing.

Reinvent this with AI

Where this one came from

Every morning we go through millions of abandoned patents and pick out 15 worth your time. This was one of today’s.

This one

+10