Clause Extraction via Machine Translation Alignment
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Solution Overview
Problem
Natural language processing models face difficulties in accurately extracting clauses from multi-clause sentences, particularly in languages like English, due to ambiguity and lack of explicit grammatical indicators.
Innovation Solution
The approach involves translating the input sentence into a target language that requires explicit grammatical indicators for dependent clauses, such as German or Russian, and using machine translation to align and extract the corresponding clauses in the original language, employing techniques like word alignment and subordinating conjunction identification.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If natural language processing models directly process sentences in ambiguous languages like English, then the processing speed is maintained, but the accuracy of clause extraction deteriorates due to lack of explicit grammatical indicators
Solution Approach 1:
The patent introduces a target language as an intermediary medium between the source language and the clause extraction process. Sentences from ambiguous languages (source language) are translated into languages with explicit grammatical indicators (target language), where clauses are clearly marked. This intermediary translation step enables accurate clause identification by leveraging the grammatical structure of the target language, which then informs the extraction of clauses from the original source language sentence.
2Measurement precision
If machine translation is used to translate sentences into target languages with explicit grammatical indicators, then clause extraction accuracy is improved, but computational resources increase
Solution Approach 1:
The patent extracts only the essential grammatical indicators (such as subordinating conjunctions and clause markers) from the translated target language sentence, rather than processing the entire translated sentence. By identifying and extracting these key markers that indicate clause boundaries, the system can determine clause positions in the source language without requiring full translation and processing of the entire target language sentence, thereby reducing computational overhead.
3Ease of operation
If grammatical indicators are inserted into translated sentences to identify dependent clauses, then clause identification becomes easier, but the complexity of the translation process increases
Solution Approach 1:
The patent applies preliminary action by training the machine translation model in advance to recognize and insert grammatical indicators at clause boundaries during the translation process. The model is pre-trained on parallel corpora with annotated clause structures, enabling it to automatically insert appropriate markers (such as commas or specific words) at relevant positions in the target language translation. This preliminary training and automatic insertion during translation simplifies the subsequent clause identification step, as the grammatical structure is already marked in the translated text.
Data Source
AI summary
A computer system extracts clauses using machine translation. An input sentence in a source language is translated into a translated sentence in a target language using a trained machine translation model, wherein the trained machine translation model inserts a grammatical indicator into a position of the translated sentence that identifies a dependent clause. The input sentence and the translated sentence are aligned to determine a position in the input sentence that corresponds to the position of the grammatical indicator in the translated sentence. The dependent clause is extracted, in the source language, from the input sentence based on the determined position in the input sentence. Embodiments of the present invention further include a method and program product for clause extraction using machine translation in substantially the same manner described above.