Document Segmentation for Precise Annotation Error Localization
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Solution Overview
Problem
Question answer systems face challenges in detecting and correcting annotation errors during document ingestion, leading to incomplete or inaccurate annotations, which can result in incorrect answers to user queries.
Innovation Solution
A knowledge manager system that iteratively segments documents into smaller segments to pinpoint annotation errors, allowing for precise identification and notification of unannotated sections, enabling developers to focus on correcting specific areas rather than entire documents.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If the knowledge manager annotates the entire document to detect annotation errors, then the error detection coverage is improved, but the time and computational resources required increase significantly
Solution Approach 1:
The patent divides the document into multiple segments and annotates only those segments that are likely to contain errors based on error patterns from previous annotations. This selective segmentation approach maintains error detection coverage while significantly reducing the time and computational resources required compared to annotating the entire document.
2Measurement precision
If the knowledge manager segments the document into many small segments to locate errors precisely, then the error localization precision is improved, but the complexity of the annotation process increases
Solution Approach 1:
The patent implements iterative segmentation where the document is divided into segments only when errors are detected, and only those segments are re-annotated. This approach achieves precise error localization without requiring the entire annotation process to be segmented, thereby managing complexity effectively.
Solution Approach 2:
Instead of segmenting and re-annotating the entire document, the patent applies partial action by re-annotating only the specific segments that contain errors or are suspected to contain errors based on error patterns. This reduces the complexity of the annotation process while maintaining high error localization precision.
3Manufacturing precision
If the knowledge manager re-annotates all document segments after detecting an error, then the annotation accuracy is improved, but the productivity of the document processing system decreases
Solution Approach 1:
The patent segments the document and re-annotates only the affected segments rather than all segments, maintaining annotation accuracy while preserving document processing throughput by minimizing the scope of re-annotation work.
Solution Approach 2:
The patent discards the annotation results for segments that are confirmed to be error-free and only recovers (re-annotates) the segments that contain errors. This approach maintains annotation accuracy while maximizing productivity by avoiding redundant re-annotation of correct segments.
Data Source
AI summary
An approach is provided in which a knowledge manager detects an annotation error while attempting to annotate a document and, as such, segments the document into multiple document segments. The knowledge manager then detects another annotation error while attempting to annotate the multiple document segments, resulting in a set of unannotated document segments. In turn, the knowledge manager generates a notification that identifies the set of unannotated document segments.