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:

UPLC and HPLC of caffeoyl esters in wild and cultivated Arctium lappa L. Analytical methods including ultra-performance liquid chromatography (UPLC) and high-performance liquid chromatography (HPLC) with photodiode array (PDA) detector were developed for the analysis of caffeoylquinic acid derivatives in seeds, leaves and roots of Arctium lappa L. Separation was performed on C(18) column utilising 5% (v/v) acetic acid in water and acetonitrile at 330 nm. Both methodologies were validated in terms of linearity, precision, and recovery. The results showed that the major advantages of UPLC, over HPLC were the fast analysis, narrow peaks, high sensitivity, and reduction of solvent consumption. Subsequently the methods were applied for the identification and quantification of chlorogenic acid (5-CQA) and 1,5-dicaffeoylquinic acid (1,5-DCQA) as main compounds in samples. The total phenolic content of samples ranged from 3.93 to 14.13 g of 5-CQA equivalent/100g dry weight (DW). There was a significant variability from 89 to 571 mg/100g for 5-CQA and 48 to 486 mg/100g for 1,5-DCQA in dry material.
{"Chemical": ["5-CQA", "acetic acid", "chlorogenic acid", "caffeoyl esters", "1,5-DCQA", "1,5-dicaffeoylquinic acid", "caffeoylquinic acid", "acetonitrile"]}