You will be shown an abstract from a biomedical research paper. Given this abstract, your task is to extract all unique entities of the following types: ["Chemical"].

Please return the output as a JSON object of the format: {"Chemical": ["Arsenic", ...]}. The keys should be entity types and values should be lists of extracted entities belonging to the corresponding type. If you cannot find entities belonging to a specific type, the value should be [].

Only output the JSON object and do not include any additional text.

Abstract:

Dispersive liquid-liquid microextraction combined with field-amplified sample stacking in capillary electrophoresis for the determination of non-steroidal anti-inflammatory drugs in milk and dairy products. Dispersive liquid-liquid microextraction (DLLME) was coupled with field-amplified sample stacking in capillary electrophoresis (FASS) for the determination of five non-steroidal anti-inflammatory drugs (NSAIDs) in bovine milk and dairy products. After extraction, the enriched analytes were back-extracted into a basic aqueous solution for injection into CE. Under optimum conditions, enrichment factors were in the range 46-229. Limits of detection of the analytes ranged from 3.0 to 13.1 μg kg(-1) for all matrices analysed. Calibration graphs showed good linearity with coefficients of determination (R(2))≥ 0.9915 and relative standard deviations (RSD%) of the analyses in the range of 0.6-6.2% (n=5). Recoveries of all NSAIDs from bottled milk, raw milk, yogurt and white cheese samples were in the ranges of 86.6-109.3%, 84.3-100.5%, 77.4-107.3%, and 90.9-101.6%, respectively. DLLME-FASS-CE was demonstrated to be a rapid and convenient method for the determination of NSAIDs in milk and dairy products.
{"Chemical": ["steroidal"]}