A prompt that combines symbolic fact extraction with executable Python code improves accuracy on a multilingual long-context 3-needle QA task, though the gains over chain-of-thought are about one percentage point and statistically untested.
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Enhancing Large Language Models with Neurosymbolic Reasoning for Multilingual Tasks
A prompt that combines symbolic fact extraction with executable Python code improves accuracy on a multilingual long-context 3-needle QA task, though the gains over chain-of-thought are about one percentage point and statistically untested.