NLP Future Event Annotation and Resolution
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Solution Overview
Problem
Current NLP systems fail to associate and track future events within documents, leading to inefficiencies in accessing relevant information when these events are completed, as they do not link or make associations between independent documents based on future event references.
Innovation Solution
A method is introduced where a future event in a document is identified using natural language processing (NLP) and associated with a unique identifier and context, allowing for the resolution of this information when the event occurs, enabling efficient retrieval of data from subsequent documents.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If current NLP systems process documents independently without tracking future events, then processing simplicity is maintained, but information association and retrieval efficiency deteriorate
Solution Approach 1:
The system performs preliminary action by creating future event annotations and storing them in a data structure during initial document processing. When a future event is detected, the system proactively creates an annotation object containing the event details and stores it in a future events data structure, preparing the information in advance so that when the event actually occurs, the system can quickly retrieve and associate the pre-prepared annotation with the completed event, eliminating the need for manual searching later.
2Productivity
If manual searches are performed across multiple documents to find completed event data, then information retrieval completeness may be achieved, but time consumption and operational efficiency deteriorate
Solution Approach 1:
The system introduces an intermediary mechanism in the form of a future events data structure that acts as a mediator between document processing and event resolution. When a future event is identified in a document, the system creates an annotation and stores it in this intermediary data structure. Later, when the event occurs, the system can efficiently retrieve the pre-stored annotation from the intermediary structure and associate it with the completed event, eliminating the need for time-consuming manual searches across multiple documents.
3Reliability
If future event references are not tracked and associated with unique identifiers, then document processing simplicity is maintained, but the ability to resolve and retrieve future event data deteriorates
Solution Approach 1:
The system applies segmentation by dividing the document processing into distinct components: identifying future events, creating separate annotation objects for each future event, storing these annotations in a dedicated future events data structure, and later retrieving and resolving them when events occur. This segmentation allows the system to reliably track future events with unique identifiers without overwhelming the entire processing system, as each component handles a specific aspect of the task independently.
Data Source
AI summary
Aspects of the invention include resolving future reference identifiers for documents. Aspects of the invention include processing a document including a reference to a future event, wherein processing includes performing natural language processing (NLP) on the document, and identifying the reference to the future event included in the document. Aspects of the invention also include generating a future reference identifier for the reference to the future event, and responsive to processing an occurrence of the future event, resolving the future reference identifier by providing data from a subsequent document for the future event associated with the future reference identifier.