An Annotated Corpus for Machine Reading of Instructions in Wet Lab Protocols

TL;DR

This paper introduces an annotated corpus of wet lab protocols to aid in converting natural language instructions into machine-readable formats, supporting automated biological research workflows.

Contribution

The paper presents a new annotated corpus of 622 wet lab protocols and demonstrates its usefulness for machine learning-based semantic parsing of instructions.

Findings

Corpus improves semantic parsing accuracy

Annotated data facilitates machine learning models

Corpus publicly available for research use

Abstract

We describe an effort to annotate a corpus of natural language instructions consisting of 622 wet lab protocols to facilitate automatic or semi-automatic conversion of protocols into a machine-readable format and benefit biological research. Experimental results demonstrate the utility of our corpus for developing machine learning approaches to shallow semantic parsing of instructional texts. We make our annotated Wet Lab Protocol Corpus available to the research community.