BenchCLAMP

BenchCLAMP是由微软语义机器开发的一个综合性基准，旨在评估语言模型在语义和句法解析任务上的表现。该数据集包含九个不同的解析数据集，涵盖了从简单的语义表示到复杂的句法结构的广泛范围。每个数据集都提供了低、中、高资源分割，以便在不同数据条件下比较语言模型的性能。BenchCLAMP支持基于提示的学习和微调，适用于评估各种语言模型，包括GPT-3等大型模型。此基准通过提供受限的解码接口，确保模型生成的输出符合预定义的语法规则，从而提高了解析任务的准确性和可靠性。

BenchCLAMP is a comprehensive benchmark developed by Microsoft Semantic Machines, designed to evaluate the performance of language models on semantic and syntactic parsing tasks. This dataset encompasses nine distinct parsing datasets, covering a broad spectrum ranging from simple semantic representations to complex syntactic structures. Each dataset provides low-, medium-, and high-resource splits, enabling the comparison of language model performance across different data conditions. BenchCLAMP supports prompt-based learning and fine-tuning, and is applicable for evaluating various language models including large-scale ones such as GPT-3. This benchmark ensures that the outputs generated by models comply with predefined grammatical rules via a constrained decoding interface, thereby improving the accuracy and reliability of parsing tasks.