Papers with seed semantic parser

1 papers
Non-Programmers Can Label Programs Indirectly via Active Examples: A Case Study with Text-to-SQL (2023.emnlp-main)

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Challenge: Using APEL, non-programmers can annotate natural language utterances with complex programs that represent their meaning.
Approach: They introduce a framework in which non-programmers select among candidate programs generated by a seed semantic parser.
Outcome: The proposed framework achieves the same annotation accuracy as the original expert annotators (75%) and exposes many subtle errors in the original annotations.

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