This repository is a research artifact from the NL2Bash project (LREC 2018), providing a dataset and neural semantic parser for translating natural language descriptions into Bash one-liners. The core contributions include a parallel corpus of ~10k NL–Bash pairs, TensorFlow-based sequence-to-sequence models with attention and copy mechanisms, a custom Bash command parser (bashlint) that normalizes commands using a grammar extracted from man pages, and evaluation tools including tree edit distance and manual judgment pipelines. The codebase is primarily a research prototype with pre-trained model checkpoints, data preprocessing scripts, and evaluation files. While the dataset and parser are valuable, the dependency on TensorFlow 1.x, JavaCC, and Python 2/3 compatibility indicates significant drift. The repository is no longer actively maintained, but the documented methodology and reusable components (e.g., tree edit distance, statistical spell checker) remain relevant for similar NL-to-code tasks.