“Psychiatric Medications Adverse Drug Events” (PMADE) corpus is an annotated corpus that has been developed using consumer health posts for psychiatric medications. This corpus consists of three main components: sentence classification, entity identification, and terminology association. We split the review posts into sentences and label them for presence of adverse drug reactions (ADRs)(2004 sentences), withdrawal symptoms (WDs) (279), drug indications (DI) 806 sentences), drug effectiveness (EF) (1078 sentences), and drug infectiveness (INF) (308 sentences). In the stage of entity identification, we identified DIs (1168 mentions), ADRs (4774 mentions) and WDs (592 mentions). Each type of the entity was further classified as physiological, psychological, cognitive, and functional. Additionally, we mapped the identified entities to the corresponding concepts in both UMLS and SNOMED CT (811 unique concepts). The quality of the corpus was measured using well-defined guidelines, double coding, high inter-annotator agreement, and final reviews by pharmacists and clinical terminologists. This corpus has implications for researchers in the area of text mining and machine learning for identifying pharmacological effects of drugs from consumer health posts and also for linking patient generated information to Electronic Health Records (EHRs).