Comparing columns in pandas different data frames and fill in a new column
I’ll take the hypothesis that your first dataframe (df) has unique company names. If so, you can easily reindex it by said company name and extract the (only one left) Main_Text Series to make it pretty much like a good old dict:

main_text = df.set_index('supplier_company_name')['Main_Text']


Now we just need to iterate over each line in samp, fetch the main text corresponding to the first column and generate a truthy value based on that and the second column. This is a job for apply:

target = samp.apply(lambda row: row[1] in main_text.loc[row[0]], axis=1)