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

    【Schema】
    【DB_ID】 college_completion
【Schema】
# Table: institution_details
[
(unitid:INTEGER, Primary Key, Examples: [100654, 100663, 100690]),
(chronname:TEXT, Examples: [Alabama A&M University]),
(city:TEXT, Examples: [Normal, Birmingham, Montgomery]),
(state:TEXT, Examples: [Alabama, Alaska, Arizona]),
(level:TEXT, Examples: [4-year, 2-year]),
(control:TEXT, Examples: [Public]),
(basic:TEXT, Examples: [Masters Colleges and Universities--larger programs]),
(hbcu:TEXT, Examples: [X, NULL]),
(flagship:TEXT, Examples: [NULL, X]),
(long_x:REAL, Examples: [-86.568502, -86.80917, -86.17401]),
(lat_y:REAL, Examples: [34.783368, 33.50223, 32.362609]),
(site:TEXT, Examples: [www.aamu.edu/]),
(student_count:INTEGER, Examples: [4051, 11502, 322]),
(awards_per_value:REAL, Examples: [14.2, 20.9, 29.9]),
(awards_per_state_value:REAL, Examples: [18.8, 17.8, 15.9]),
(awards_per_natl_value:REAL, Examples: [21.5, 22.5, 16.5]),
(exp_award_value:INTEGER, Examples: [105331, 136546, 58414]),
(exp_award_state_value:INTEGER, Examples: [75743, 92268, 42194]),
(exp_award_natl_value:INTEGER, Examples: [66436, 101725, 37780]),
(exp_award_percentile:INTEGER, Examples: [90, 97, 30]),
(ft_pct:REAL, Examples: [93.8, 72.7, 62.7]),
(fte_value:INTEGER, Examples: [3906, 10032, 294]),
(fte_percentile:INTEGER, Examples: [33, 67, 12]),
(med_sat_value:TEXT, Examples: [823, 1146, NULL]),
(med_sat_percentile:TEXT, Examples: [0, 84, NULL]),
(aid_value:INTEGER, Examples: [7142, 6088, 2540]),
(aid_percentile:INTEGER, Examples: [72, 50, 1]),
(endow_value:TEXT, Examples: [NULL, 24136, 302]),
(endow_percentile:TEXT, Examples: [NULL, 93, 1]),
(grad_100_value:REAL, Examples: [10.0, 29.4, 0.0]),
(grad_100_percentile:INTEGER, Examples: [15, 67, 0]),
(grad_150_value:REAL, Examples: [29.1, 53.5, 66.7]),
(grad_150_percentile:INTEGER, Examples: [14, 66, 72]),
(pell_value:REAL, Examples: [71.2, 35.1, 68.4]),
(pell_percentile:INTEGER, Examples: [98, 39, 91]),
(retain_value:REAL, Examples: [63.1, 80.2, 37.5]),
(retain_percentile:INTEGER, Examples: [17, 70, 2]),
(ft_fac_value:REAL, Examples: [82.8, 92.4, 67.2]),
(ft_fac_percentile:INTEGER, Examples: [89, 98, 71]),
(vsa_year:TEXT, Examples: [2010, 2011, NULL]),
(vsa_grad_after4_first:TEXT, Examples: [14.7, 22.3, NULL]),
(vsa_grad_elsewhere_after4_first:TEXT, Examples: [2, 2.9, NULL]),
(vsa_enroll_after4_first:TEXT, Examples: [36.5, 34.2, NULL]),
(vsa_enroll_elsewhere_after4_first:TEXT, Examples: [16.1, 19.2, NULL]),
(vsa_grad_after6_first:TEXT, Examples: [33, 42.6, NULL]),
(vsa_grad_elsewhere_after6_first:TEXT, Examples: [5.3, 10.5, NULL]),
(vsa_enroll_after6_first:TEXT, Examples: [12.5, 7.9, NULL]),
(vsa_enroll_elsewhere_after6_first:TEXT, Examples: [14.6, 13.1, NULL]),
(vsa_grad_after4_transfer:TEXT, Examples: [15.7, NULL, 0]),
(vsa_grad_elsewhere_after4_transfer:TEXT, Examples: [1.5, NULL, 0]),
(vsa_enroll_after4_transfer:TEXT, Examples: [40.9, NULL, 0]),
(vsa_enroll_elsewhere_after4_transfer:TEXT, Examples: [17.2, NULL, 0]),
(vsa_grad_after6_transfer:TEXT, Examples: [36.4, NULL, 0]),
(vsa_grad_elsewhere_after6_transfer:TEXT, Examples: [5.6, NULL, 0]),
(vsa_enroll_after6_transfer:TEXT, Examples: [17.2, NULL, 0]),
(vsa_enroll_elsewhere_after6_transfer:TEXT, Examples: [11.1, NULL, 0]),
(similar:TEXT),
(state_sector_ct:INTEGER, Examples: [13, 16, 25]),
(carnegie_ct:INTEGER, Examples: [386, 106, 252]),
(counted_pct:TEXT, Examples: [99.7|07, 56.0|07, 100.0|07]),
(nicknames:TEXT, Examples: [NULL, UAB, UAH]),
(cohort_size:INTEGER, Examples: [882, 1376, 3])
]
# Table: state_sector_grads
[
(stateid:INTEGER, Examples: [1, 2, 4]),
(state:TEXT, Examples: [Alabama, Alaska, Arizona]),
(state_abbr:TEXT, Examples: [AL, AK, AZ]),
(control:TEXT, Examples: [Private for-profit]),
(level:TEXT, Examples: [4-year, 2-year]),
(year:INTEGER, Examples: [2011, 2012, 2013]),
(gender:TEXT, Examples: [B, F, M]),
(race:TEXT, Examples: [A, Ai, B]),
(cohort:TEXT, Examples: [4y bach, 4y other, 2y all]),
(grad_cohort:TEXT, Examples: [0, 1, 51]),
(grad_100:TEXT, Examples: [0, 2, 15]),
(grad_150:TEXT, Examples: [0, 3, 18]),
(grad_100_rate:TEXT, Examples: [NULL, 0, 3.9]),
(grad_150_rate:TEXT, Examples: [NULL, 0, 5.9]),
(grad_cohort_ct:INTEGER, Examples: [9, 16, 13])
]
# Table: institution_grads
[
(unitid:INTEGER, Examples: [100760, 101028, 101143]),
(year:INTEGER, Examples: [2011, 2012, 2013]),
(gender:TEXT, Examples: [B, M, F]),
(race:TEXT, Examples: [X, W, B]),
(cohort:TEXT, Examples: [2y all, 4y other, 4y bach]),
(grad_cohort:TEXT, Examples: [446, 185, 261]),
(grad_100:TEXT, Examples: [73, NULL, 40]),
(grad_150:TEXT, Examples: [105, 40, 65]),
(grad_100_rate:TEXT, Examples: [16.4, NULL, 6.7]),
(grad_150_rate:TEXT, Examples: [23.5, 21.6, 24.9])
]
# Table: state_sector_details
[
(stateid:INTEGER, Primary Key, Examples: [0, 1, 2]),
(state:TEXT, Examples: [United States, Alabama, Alaska]),
(state_post:TEXT, Examples: [U.S., Ala., Alaska]),
(level:TEXT, Primary Key, Examples: [2-year, 4-year]),
(control:TEXT, Primary Key, Examples: [Private for-profit]),
(schools_count:INTEGER, Examples: [632, 1180, 527]),
(counted_pct:TEXT, Examples: [NULL, 61, 62]),
(awards_per_state_value:TEXT, Examples: [NULL, 18.8, 17.8]),
(awards_per_natl_value:REAL, Examples: [21.5, 22.5, 24.6]),
(exp_award_state_value:TEXT, Examples: [NULL, 75743, 92268]),
(exp_award_natl_value:INTEGER, Examples: [66436, 101725, 38763]),
(state_appr_value:TEXT, Examples: [NULL, 290.68, 496.78]),
(state_appr_rank:TEXT, Examples: [NULL, 11, 2]),
(grad_rate_rank:TEXT, Examples: [23, 18, 8]),
(awards_per_rank:TEXT, Examples: [NULL, 42, 49])
]
【Foreign keys】
state_sector_grads.state=institution_details.state
state_sector_grads.stateid=state_sector_details.stateid
institution_grads.unitid=institution_details.unitid
state_sector_details.state=institution_details.state

    【Question】
    List the site of institution within the student count of 500 to 1000 that has the recent year of data release. recent year of data release refers to newest year;

    【Evidence】
    recent year of data release refers to newest year;

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

SQL: SELECT DISTINCT T1.site FROM institution_details AS T1 INNER JOIN institution_grads AS T2 ON T2.unitid = T1.unitid WHERE T1.student_count BETWEEN 500 AND 1000 AND T2.year = ( SELECT MAX(T2.year) FROM institution_details AS T1 INNER JOIN institution_grads AS T2 ON T2.unitid = T1.unitid )