According to an aspect, document-based requirement identification and extraction includes parsing a set of documents and identifying relationships among parsed components of the documents and applying the parsed components and identified relationships to a meta-model that defines requirements. The requirements include a statement expressing a need and/or responsibility. A further aspect includes identifying candidate requirements and their candidate topics from results of the applying. For each of the identified candidate topics, a feature vector is built from the corresponding candidate requirements. A further aspect includes training the meta-model with the feature vectors, validating the meta-model, and classifying output of the validating to identify a subset of the candidate requirements, and corresponding topics expressed in the set of documents.