Cross-lingual Information Extraction via Semantic Mapping
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Solution Overview
Problem
Current information extraction systems require labor-intensive rule creation for each language, making it difficult to extract structured information from unstructured text across multiple languages due to unique sentence structures and language rules.
Innovation Solution
A cross-lingual information extraction program is constructed by parsing text using language-specific semantic parsers to create language-specific representations, which are then mapped to a single cross-lingual semantic representation, allowing a single program to extract information from texts in various languages.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If language-specific rules are created for each language, then information extraction accuracy for that language is improved, but the complexity and labor required to maintain multiple rule sets increases
Solution Approach 1:
The patent creates a universal information extraction program that can process multiple languages through a single interface. The system maintains language-specific semantic parsers and representations internally but presents a unified extraction interface, allowing one program to serve multiple language functions without requiring separate rule sets for each language.
Solution Approach 2:
The patent introduces language-specific semantic representations as intermediary layers between the input text and the universal extraction program. These representations act as mediators that translate different language structures into a common format that the single extraction program can process, eliminating the need for multiple language-specific extraction programs.
2Ease of operation
If a single information extraction program is used across multiple languages, then the ease of operation and maintenance is improved, but the ability to accurately handle language-specific sentence structures deteriorates
Solution Approach 1:
The patent segments the information extraction system into distinct components: language-specific semantic parsers that handle language-specific structures, language-specific semantic representations that capture linguistic nuances, and a universal extraction program that performs the actual information extraction. This segmentation allows each component to specialize in its function while working together as a unified system.
Solution Approach 2:
The patent adds a dimensional layer to the extraction system by introducing language-specific semantic representations as an intermediate dimension between the input text and the extraction program. This additional dimension allows the system to preserve language-specific information while maintaining a unified extraction interface, effectively solving the contradiction between simplicity and accuracy.
3Adaptability or versatility
If multiple language-specific extraction programs are developed, then coverage of different languages is improved, but the time and resources required for development and maintenance increase
Solution Approach 1:
The patent develops a universal extraction program that can process multiple languages through a single interface. By maintaining language-specific semantic parsers and representations internally, the system achieves multi-language capability without requiring separate extraction programs for each language, significantly reducing development and maintenance time.
Solution Approach 2:
The patent performs preliminary action by pre-processing the input text through language-specific semantic parsers that generate language-specific semantic representations. This preliminary processing captures language-specific structures and nuances before the universal extraction program processes the information, enabling accurate multi-language extraction without requiring multiple full extraction programs.
Data Source
AI summary
One embodiment provides method for constructing a cross-lingual information extraction program, the method including: utilizing at least one processor to execute computer code that performs the steps of: constructing a plurality of language-specific representations from text expressed in a plurality of languages by parsing the text of each language using a language-specific semantic parser; mapping the plurality of language-specific representations to a single cross-lingual semantic representation, wherein the cross-lingual semantic representation encompasses the plurality of languages; and constructing the cross-lingual information extraction program based on the cross-lingual semantic representation. Other aspects are described and claimed.