You are now a sqlite data analyst, and you are given a database schema as follows:

    【Schema】
    【DB_ID】 retails
【Schema】
# Table: customer
[
(c_custkey:INTEGER, Primary Key, Examples: [1, 2, 3]),
(c_mktsegment:TEXT, Examples: [BUILDING, MACHINERY, FURNITURE]),
(c_nationkey:INTEGER, Examples: [8, 16, 11]),
(c_name:TEXT, Examples: [Customer#000000001, Customer#000000002, Customer#000000003]),
(c_address:TEXT, Examples: [KwX3hMHjZ6, ioUn,eqTTXOdo, YddJqmIdouNT9Yj]),
(c_phone:TEXT, Examples: [937-241-3198, 906-965-7556, 328-750-7603]),
(c_acctbal:REAL, Examples: [3560.03, 7550.21, -926.96]),
(c_comment:TEXT)
]
# Table: supplier
[
(s_suppkey:INTEGER, Primary Key, Examples: [1, 2, 3]),
(s_nationkey:INTEGER, Examples: [13, 5, 22]),
(s_comment:TEXT),
(s_name:TEXT, Examples: [Supplier#000000001, Supplier#000000002, Supplier#000000003]),
(s_address:TEXT, Examples: [,wWs4pnykQOFl8mgVCU8EZMXqZs1w]),
(s_phone:TEXT, Examples: [800-807-9579, 348-617-6055, 471-986-9888]),
(s_acctbal:REAL, Examples: [3082.86, 3009.73, 9159.78])
]
# Table: region
[
(r_regionkey:INTEGER, Primary Key, Examples: [0, 1, 2]),
(r_name:TEXT, Examples: [AFRICA, AMERICA, ASIA]),
(r_comment:TEXT)
]
# Table: orders
[
(o_orderdate:DATE, Examples: [1995-04-19]),
(o_orderkey:INTEGER, Primary Key, Examples: [1, 2, 3]),
(o_custkey:INTEGER, Examples: [73100, 92861, 44875]),
(o_orderpriority:TEXT, Examples: [4-NOT SPECIFIED, 1-URGENT, 5-LOW]),
(o_shippriority:INTEGER, Examples: [0]),
(o_clerk:TEXT, Examples: [Clerk#000000916, Clerk#000000373, Clerk#000000485]),
(o_orderstatus:TEXT, Examples: [P, O, F]),
(o_totalprice:REAL, Examples: [203198.56, 317719.99, 146674.98]),
(o_comment:TEXT)
]
# Table: part
[
(p_partkey:INTEGER, Primary Key, Examples: [1, 2, 3]),
(p_type:TEXT, Examples: [LARGE PLATED TIN]),
(p_size:INTEGER, Examples: [31, 4, 30]),
(p_brand:TEXT, Examples: [Brand#43, Brand#55, Brand#53]),
(p_name:TEXT, Examples: [burlywood plum powder puff mint]),
(p_container:TEXT, Examples: [LG BAG, LG CASE, WRAP CASE]),
(p_mfgr:TEXT, Examples: [Manufacturer#4, Manufacturer#5, Manufacturer#1]),
(p_retailprice:REAL, Examples: [901.0, 902.0, 903.0]),
(p_comment:TEXT, Examples: [blithely busy reque])
]
# Table: lineitem
[
(l_shipdate:DATE, Examples: [1995-08-16]),
(l_orderkey:INTEGER, Primary Key, Examples: [1, 2, 4]),
(l_discount:REAL, Examples: [0.1, 0.09, 0.02]),
(l_extendedprice:REAL, Examples: [58303.08, 16947.7, 63642.9]),
(l_suppkey:INTEGER, Examples: [6296, 8776, 3859]),
(l_quantity:INTEGER, Examples: [33, 10, 34]),
(l_returnflag:TEXT, Examples: [N, A, R]),
(l_partkey:INTEGER, Examples: [98768, 23771, 113858]),
(l_linestatus:TEXT, Examples: [O, F]),
(l_tax:REAL, Examples: [0.06, 0.08, 0.07]),
(l_commitdate:DATE, Examples: [1995-07-12]),
(l_receiptdate:DATE, Examples: [1995-09-14]),
(l_shipmode:TEXT, Examples: [RAIL, TRUCK, SHIP]),
(l_linenumber:INTEGER, Primary Key, Examples: [1, 2, 3]),
(l_shipinstruct:TEXT, Examples: [NONE, TAKE BACK RETURN, COLLECT COD]),
(l_comment:TEXT, Examples: [carefully bo])
]
# Table: nation
[
(n_nationkey:INTEGER, Primary Key, Examples: [0, 1, 2]),
(n_name:TEXT, Examples: [ALGERIA, ARGENTINA, BRAZIL]),
(n_regionkey:INTEGER, Examples: [0, 1, 3]),
(n_comment:TEXT)
]
# Table: partsupp
[
(ps_partkey:INTEGER, Primary Key, Examples: [1, 2, 3]),
(ps_suppkey:INTEGER, Primary Key, Examples: [2, 2502, 5002]),
(ps_supplycost:REAL, Examples: [400.75, 702.61, 383.95]),
(ps_availqty:INTEGER, Examples: [1111, 3999, 7411]),
(ps_comment:TEXT)
]
【Foreign keys】
customer.c_nationkey=nation.n_nationkey
supplier.s_nationkey=nation.n_nationkey
orders.o_custkey=customer.c_custkey
lineitem.l_orderkey=orders.o_orderkey
lineitem.l_partkey=partsupp.ps_partkey
lineitem.l_suppkey=partsupp.ps_suppkey
nation.n_regionkey=region.r_regionkey
partsupp.ps_partkey=part.p_partkey
partsupp.ps_suppkey=supplier.s_suppkey

    【Question】
    Which part has a bigger size, "pink powder drab lawn cyan" or "cornflower sky burlywood green beige"? size refers to p_size; "pink powder drab lawn cyan" or "cornflower sky burlywood green beige" refers to p_name in ('pink powder drab lawn cyan', 'cornflower sky burlywood green beige')

    【Evidence】
    size refers to p_size; "pink powder drab lawn cyan" or "cornflower sky burlywood green beige" refers to p_name in ('pink powder drab lawn cyan', 'cornflower sky burlywood green beige')

    Please read and understand the database schema carefully, and generate an executable SQL based on the user's question and evidence. 

SQL: SELECT T.p_name FROM ( SELECT p_name, p_size FROM part WHERE p_name IN ('pink powder drab lawn cyan', 'cornflower sky burlywood green beige') ) AS T ORDER BY p_size DESC LIMIT 1