Input Text Correction for Question Answering Systems
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Solution Overview
Problem
Conventional question answering systems face processing issues due to inconsistencies in unstructured input text, such as abbreviations, irrelevant information, misspelled words, anomalies, and bad grammar, which can hinder effective analysis and answer generation.
Innovation Solution
The system applies corrective measures to the original input text to create revised text, addressing issues like spelling correction, abbreviation expansion, removing irrelevant information, and grammatical corrections, while maintaining annotations to recreate the original text for transparency and user feedback.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If corrective measures are applied to preprocess input text, then processing accuracy is improved, but processing time increases
Solution Approach 1:
The system applies corrective measures (spelling correction, abbreviation expansion, grammar correction) to the input text before the main question answering processing. This preliminary action prepares the text in advance, ensuring higher accuracy during subsequent analysis while managing processing time through efficient pre-processing
Solution Approach 2:
The text processing is divided into separate correction modules (spelling correction, abbreviation expansion, grammar correction) that can process different aspects of the input text independently. This segmentation allows for targeted processing and optimization of each correction type, improving overall accuracy while managing time consumption
2Loss of information
If the original text is recreated with annotations, then transparency is improved, but system complexity increases
Solution Approach 1:
The system creates a copy of the original input text and adds annotations to it, rather than modifying the original text directly. This copying approach maintains transparency by preserving the original text for comparison while adding correction information, without requiring complex restructuring of the system architecture
Solution Approach 2:
Annotations serve as an intermediary layer between the original text and the processed text. They provide transparency by showing what corrections were made without requiring the system to fundamentally change its processing architecture, thus managing complexity while improving transparency
Data Source
AI summary
A technique of improving input text processing in a data processing system that answers questions includes receiving a question from a user. The question has associated supporting original input text that is utilized in answering the question. Corrective measures are applied to the supporting original input text to create supporting revised input text. The supporting revised input text documents corrective measures applied to the supporting original input text. An answer to the question is generated based on, at least in part, the supporting revised input text. The supporting original input text is recreated from the supporting revised input text based on the documented corrective measures in the supporting revised input text subsequent to generating the answer. The answer and the supporting original input text as recreated are transmitted to the user.