  Large language models (LLMs) serve as powerful tools for design, providing
capabilities for both task automation and design assistance. Recent
advancements have shown tremendous potential for facilitating LLM integration
into the chip design process; however, many of these works rely on data that
are not publicly available and/or not permissively licensed for use in LLM
training and distribution. In this paper, we present a solution aimed at
bridging this gap by introducing an open-source dataset tailored for OpenROAD,
a widely adopted open-source EDA toolchain. The dataset features over 1000 data
points and is structured in two formats: (i) a pairwise set comprised of
question prompts with prose answers, and (ii) a pairwise set comprised of code
prompts and their corresponding OpenROAD scripts. By providing this dataset, we
aim to facilitate LLM-focused research within the EDA domain. The dataset is
available at https://github.com/OpenROAD-Assistant/EDA-Corpus.
