1913 — Page 526

The user wants me to proofread OCR output of a historical prison record from Hong Kong (1913). The text appears to be a table showing weekly prisoner counts for Europeans and Chinese/Coloured, separated by gender.

Let me analyze the structure:

• It's a table with columns for Europeans (Males, Females) and Chinese/Coloured (Males, Females), with Weekly and Total columns
• The data is organized by week dates throughout 1913
• There are many OCR errors: garbled characters, misaligned columns, broken numbers, etc.

I need to reconstruct this as a proper Markdown table. Let me parse the data carefully.

First, let me understand the column headers:

• EUROPEANS: Males, Females, Weekly, Total
• CHINESE OR COLOURED: Males, Females, Weekly, Total

Wait, looking at the header row:

"EUROPEANS. CHINESE OR COLOURED. EUROPEANS. CHINESE OR COLOURED. WEEKLY. TOTAL. WEEKLY. TOTAL. Males. Fe- males. Males. Fe- males. Males. Fe- males. Males. Fe- males."

This seems like the headers got duplicated. Let me interpret:

The table likely has:

• Date
• Europeans: Males, Females, Weekly Total
• Chinese/Coloured: Males, Females, Weekly Total
• Or perhaps: Europeans Males, Europeans Females, Chinese Males, Chinese Females, and then totals

Actually, looking at the data rows, each row seems to have:

Date | Euro Males | Euro Females | Chinese Males | Chinese Females | Euro Weekly | Euro Total | Chinese Weekly | Chinese Total

But the numbers don't quite match. Let me look at the first data row:

"January 5 12 I 681 12 12 687 3333333 30 724"

This is messy. "I" is probably "1" (one female European). "3333333" is clearly garbage. "30 724" might be Chinese weekly/total.

Let me try to reconstruct systematically. The table appears to have weekly data for each week of 1913. Each week has a date (usually Sunday or Saturday).

I'll need to clean up each row. This is going to be extensive. Let me go through week by week.

First, let me note the structure from the header:

The header shows:

EUROPEANS. CHINESE OR COLOURED. EUROPEANS. CHINESE OR COLOURED. WEEKLY. TOTAL. WEEKLY. TOTAL. Males. Fe- males. Males. Fe- males. Males. Fe- males. Males. Fe- males.

This suggests 8 data columns plus date:

1. Europeans Males
2. Europeans Females
3. Chinese/Coloured Males
4. Chinese/Coloured Females
5. Europeans Weekly
6. Europeans Total
7. Chinese/Coloured Weekly
8. Chinese/Coloured Total

But "Weekly" and "Total" might be the same thing? Or "Weekly" is the weekly count and "Total" is cumulative? Given the context "RETURN showing the NUMBER of PRISONERS on the last Day of each Week", it's likely a snapshot each week, so Weekly = Total for that week.

Actually, looking at the numbers: for Jan 5, Europeans: 12 males, 1 female = 13 total. Chinese: 681 males, 12 females = 693 total. But the row shows "12 687 3333333 30 724". 12+1=13, not 12. 681+12=693, not 687. Hmm.

Wait: "12 I 681 12" -> 12 Euro M, 1 Euro F, 681 Chinese M, 12 Chinese F. Then "12 687" might be Euro weekly (13?) and total? No.

Let me look at July 6 row: "July 6 13 35 735 13 12". That would be 13 Euro M, 35 Euro F? That seems high for Euro females. Or maybe columns shifted.

Actually, the header says "Males. Fe- males." for each group. So:

Col1: Euro Males

Col2: Euro Females

Col3: Chinese Males

Col4: Chinese Females

Col5: Euro Weekly

Col6: Euro Total

Col7: Chinese Weekly

Col8: Chinese Total

But for Jan 5: 12, 1, 681, 12, 12, 687, 3333333, 30, 724 -> that's 9 numbers after date. Too many.

Maybe the "WEEKLY. TOTAL." are subheaders for each group? Like:

EUROPEANS: WEEKLY, TOTAL

CHINESE OR COLOURED: WEEKLY, TOTAL

And each has Males, Females.

So 4 columns per group? No.

Let me search for similar historical documents. This looks like a "Return showing the number of prisoners on the last day of each week" - a standard colonial prison statistical return. Typically these have:

Date | European M | European F | Indian M | Indian F | Chinese M | Chinese F | Total M | Total F | Grand Total

Or something similar.

But the header explicitly says "EUROPEANS. CHINESE OR COLOURED." only two groups.

Given the OCR mess, I think the best approach is to reconstruct the table as it appears in the OCR, cleaning up obvious errors, and presenting it in a readable Markdown table with the columns as they seem to be intended.

Let me parse row by row, making best guesses.

I'll create a table with columns: Date, Euro_M, Euro_F, Chinese_M, Chinese_F, Euro_Weekly, Euro_Total, Chinese_Weekly, Chinese_Total

But many rows have fewer or more numbers. I'll need to infer.

Actually, looking at the pattern, each week entry seems to have the date followed by 8 numbers (2 groups × 2 genders × 2 metrics?).

Let me count numbers in first few rows:

Jan 5: "12 I 681 12 12 687 3333333 30 724" -> 9 numbers (I=1)

Jan 12: "19 12 687 41 741 20 12" -> 7 numbers

Jan 19: "26 12 721 35 769 27 11" -> 7 numbers

Jan 26: ": : 655 53 721 675 46 738" -> 8 numbers (:: maybe 0 0 or ditto)

Feb 2: "14 2 708 40 764" -> 5 numbers

Feb 9: "16 668 38 723 10 13 641 46 700" -> 9 numbers

Feb 16: "15 1 669 39 724 17 13 676 44 738" -> 10 numbers

Feb 23: "13 648 35 697 24 14" -> 6 numbers

Mar 2: "14 636 37 688 31 18 625 38 681" -> 9 numbers

Mar 9: "14 = 1 662 42 719" -> 6 numbers (=1 maybe 11?)

Mar 16: "11 627 3N 676 14 12 633 39 15 684" -> 10 numbers (3N=31?)

Mar 23: "23 621 38 668 21 14" -> 6 numbers

Mar 30: "9 629 34 671 28 14" -> 6 numbers

Apr 6: "9 596 42 647" -> 4 numbers

Apr 13: "10 654 48 712 12 13 1+ 1 595 35 644" -> 10 numbers (1+ = 11?)

Apr 20: "20 10 651 18 709 19 12 570 37 620" -> 9 numbers

Apr 27: "9 645 11 640" -> 4 numbers (wait "11 640" but header shows Chinese females? 11 females?)

May 4: "10 660 ++ 46 700 48 718" -> 7 numbers (++ = 11? or 22?)

May 11: "14 = 716 53 789 9 10 610 3R 658" -> 9 numbers (= = 11? 3R=38?)

May 18: "30 23 18 15 695 761 16 12 625 36 673" -> 11 numbers

May 25: "16 681 50 747 23 11 599 31 644" -> 9 numbers

Jun 1: "14 725 : 44 783 30 11 562 42 615" -> 9 numbers (: = ?)

Jun 8: "14 710 45 799 14 11 561 38 613" -> 8 numbers

Jun 15: "16 4 738 47 801 22 17 715 48 780" -> 10 numbers (16 4 = 16 males, 4 females?)

Jun 22: "21 12 551 35 601 29 16 670 53 335 739" -> 10 numbers (335 739?)

Jun 29: "11 537 32 580" -> 4 numbers

Jul 6: "13 35 735 13 12" -> 5 numbers

Jul 13: "20 12 709" wait no, Jul 6 row continues? "July 6 13 35 735 13 12" then next line "20 12 709" is probably Jul 13? But the text shows:

"July

6

13

35

735

13

12

"

19

12

687

41

741

20

12

J

北

26

12

721

35

769

27

11"

This is very garbled. The OCR has broken lines randomly.

Given the complexity, I think the best approach is to present the data as a cleaned-up table with the columns that make sense, noting where data is uncertain. But the user wants me to proofread and reconstruct.

Given the instruction: "If data is clearly in table format, reconstruct the table using Markdown table syntax."

I should create a Markdown table with consistent columns. Let me define columns based on the header:

The header lists:

• EUROPEANS: Males, Females
• CHINESE OR COLOURED: Males, Females
• EUROPEANS: WEEKLY, TOTAL
• CHINESE OR COLOURED: WEEKLY, TOTAL

But that's redundant. Perhaps the table has two sections: one for Europeans (with weekly and total), one for Chinese (with weekly and total), each split by gender.

Actually, "WEEKLY" and "TOTAL" might be the same column labeled twice? Or "WEEKLY" is the count for that week, "TOTAL" is cumulative for the year? But the title says "on the last Day of each Week", so it's a weekly snapshot.

I think the most logical structure is:

Date | European Males | European Females | European Total | Chinese Males | Chinese Females | Chinese Total

But the header shows "WEEKLY. TOTAL." for each group. Maybe "Weekly" means the weekly admission/discharge? No, it says "NUMBER of PRISONERS on the last Day of each Week".

Let me look at the numbers: For Jan 5, if Euro M=12, Euro F=1, Total=13. Chinese M=681, Chinese F=12, Total=693. The row shows "12 687 3333333 30 724". 12 and 687? 687 is close to 693-6? Not sure.

Another idea: The columns might be:

1. European Males
2. European Females
3. Chinese Males
4. Chinese Females
5. Total Males (European+Chinese)
6. Total Females
7. Grand Total

But header doesn't suggest that.

Given the time, I'll reconstruct a table with the following columns based on the most consistent data pattern:

Date, Euro_M, Euro_F, Chinese_M, Chinese_F, Euro_Total, Chinese_Total

And I'll compute totals where missing. I'll clean obvious OCR errors (like "I"->"1", "N"->"1" or "7", "J"->"1", "北"->"", "༣"->"", "ก"->"", "="->"11", "++"->"11", "3N"->"31", "3R"->"38", "1+"->"11", "JJ"->"11", "F"->"", "Л"->"", "铃"->"", ">>"->"", "F"->"", "**"->"", "•"->"", ":"->"", "="->"", "北"->"", "J"->"", "ວາ"->"", "2223"->"", "3333333"->"").

I'll go through each week systematically. There are 52 weeks in 1913. Let me list the dates mentioned:

Jan 5, 12, 19, 26

Feb 2, 9, 16, 23

Mar 2, 9, 16, 23, 30

Apr 6, 13, 20, 27

May 4, 11, 18, 25

Jun 1, 8, 15, 22, 29

Jul 6, 13, 20, 27

Aug 3, 10, 17, 24, 31

Sep 7, 14, 21, 28

Oct 5, 12, 19, 26

Nov 2, 9, 16, 23, 30

Dec 7, 14, 21, 28

That's 53 weeks? 1913 started on Wednesday, so Jan 5 is first Sunday. 52 weeks would end Dec 28. Dec 28 is listed.

Now, let me parse each row from the OCR text, line by line as presented.

The OCR text is a single block. I'll split by lines and parse.

But the user gave the text as a single message. I need to parse it as best I can.

Given the complexity, I'll produce a Markdown table with the data cleaned up, using ... for missing/unclear values.

Let me start building the table row by row from the OCR.

I'll write a script in my mind to parse.

First, the header row in markdown:

But the original has "WEEKLY" and "TOTAL" for each. Maybe I should include Weekly and Total as separate? But they seem to be the same for a snapshot.

Looking at Jan 5: "12 I 681 12 12 687 3333333 30 724"

If Euro M=12, Euro F=1, Chinese M=681, Chinese F=12.

Then Euro Total = 13, Chinese Total = 693.

But we have "12 687" - maybe Euro Weekly=12? No.

"3333333 30 724" - garbage.

Jan 12: "19 12 687 41 741 20 12"

Euro M=19, Euro F=12? That would be 31 Europeans, seems high. Chinese M=687, Chinese F=41, Chinese Total=728? But 741 given. 20 12 maybe next week?

Actually, the data might be arranged in two columns per page? The OCR might have read two columns side by side as one.

The text shows "January 5" then numbers, then "19" on next line? No, the text is:

"January 5

12

I

681

12

12

687

3333333

30

724

July

6

13

35

735

13

12

"

19

12

687

41

741

20

12

J

北

26

12

721

35

769

27

11"

This is completely jumbled. "July 6" appears right after Jan 5 data. Then "19" (Jan 19?) appears after July 6 data.

It seems the OCR read the page in column-major order: left column (Jan-Apr?), right column (Jul-Oct?), but mixed.

The document likely has two columns on the page: left column for first half of year, right column for second half. OCR read top to bottom left column, then top to bottom right column, but the text provided interleaves them? Actually, the text shows Jan 5, then July 6, then Jan 19, then Jan 26, then Feb 2, then Aug 3, etc. Let me check:

After "27 11" (end of Jan?), then:

":

:

655

53

721

675

46

738

691

49

752

63N

41

"

693

J

February 2

14

2

708

40

764

Angust

3

13

626

41

683

9

16

668

38

723

10

13

641

46

700

"

16

15

1

669

39

724

17

13

676

44

"

"

738

23

13

648

35

697

24

14

J

༣

ก

630

36

680

March 2

14

636

37

688

31

18

625

38

"

681

9

14

=

1

662

42

719

Sept.

7

15

654

38

707

14

12

633

39

15

684

23

621

38

668

21

14

J

1

613

36

664

30

9

629

34

671

"

28

14

H

1

630

39

684

April

6

9

596

42

647

October 5

13

614

36

664

12

13

1+

1

595

35

644

"}

20

20

10

651

18

709

19

12

570

"

37

620

•

27

9

645

11

ང

May

4

10

660

++

46

700

48

718

Nov. 2

10

609

35

654

11

14

"

=

716

53

789

9

JJ

10

610

3R

658

JJ

F

30 23

18

15

695

761

16

12

Л

625

36

673

25

16

681

50

747

23

**

11

599

31

644

June

I

14

725

:

44

783

30

11

562

42

615

8

14

710

45

799

14

>>

11

561

38

613

=

2223

17

715

48

780

21

12

"F

551

35

601

29

16

670

53

335

739

28

11

"

537

32

580"

The pattern: The text alternates between first-half months (Jan, Feb, Mar, Apr, May, Jun) and second-half months (Jul, Aug, Sept, Oct, Nov, Dec). For example:

• Jan 5 data, then Jul 6 data
• Jan 19 data, then Jan 26 data? Wait, after Jul 6, we have "19 12 687 41 741 20 12" which is likely Jan 19.
• Then "26 12 721 35 769 27 11" Jan 26.
• Then ":: 655 53 721 675 46 738 691 49 752 63N 41 693" - this might be Feb 2? But Feb 2 appears later with "February 2 14 2 708 40 764".
• Then "February 2" appears, then "Angust 3" (August 3).
• Then "9 16 668 38 723 10 13 641 46 700" - Feb 9 and Feb 16?
• Then "16 15 1 669 39 724 17 13 676 44 738" - Feb 16 and Feb 17? Wait Feb 17 is not a week end.
• Then "23 13 648 35 697 24 14 630 36 680" - Feb 23 and Feb 24?
• Then "March 2" then "31 18 625 38 681" - Mar 2 and Mar 31?
• Then "9 14 = 1 662 42 719" - Mar 9?
• Then "Sept. 7" appears.
• Then "14 12 633 39 15 684 23 621 38 668 21 14 1 613 36 664 30 9 629 34 671" - multiple March weeks?
• Then "28 14 H 1 630 39 684" - Mar 28?
• Then "April 6" then "October 5"
• Then "12 13 1+ 1 595 35 644" - Apr 13?
• Then "20 20 10 651 18 709 19 12 570 37 620" - Apr 20?
• Then "27 9 645 11" - Apr 27?
• Then "May 4" then "Nov. 2"
• Then "11 14 = 716 53 789 9 10 610 3R 658" - May 11?
• Then "30 23 18 15 695 761 16 12 625 36 673" - May 18? (30 23 = 30th? but May 30 is not a week end)
• Then "25 16 681 50 747 23 11 599 31 644" - May 25?
• Then "June I 14 725 : 44 783 30 11 562 42 615" - Jun 1?
• Then "8 14 710 45 799 14 11 561 38 613" - Jun 8?
• Then "2223 17 715 48 780 21 12 551 35 601 29 16 670 53 335 739" - Jun 15, 22, 29?
• Then "28 11 537 32 580" - Jun 28? but Jul 6 already done.

This is extremely messy. The OCR has completely scrambled the two columns.

Given the instructions, I need to produce a proofread text in Markdown. The primary task is to reconstruct sentences and paragraphs, but this is a table. For tables, reconstruct using Markdown table syntax.

I think the best I can do is to create a table with all the weeks in chronological order, extracting data from this mess as best as possible, marking uncertain cells with ... or notes.

But the user said: "Do not add any commentary, notes, or explanations." So I cannot add notes. I must only output the Markdown table.

I could output the table with the data as cleaned, leaving blank or ... for missing.

Given the complexity, perhaps the expected output is to recognize this as a table and format it nicely, correcting obvious OCR errors, but keeping the structure as a single table with the columns as they appear in the header.

Let me try to define the columns from the header:

The header line: "EUROPEANS. CHINESE OR COLOURED. EUROPEANS. CHINESE OR COLOURED. WEEKLY. TOTAL. WEEKLY. TOTAL. Males. Fe- males. Males. Fe- males. Males. Fe- males. Males. Fe- males."

This suggests 16 columns? No, it's listing the column headers in sequence:

1. EUROPEANS (group)
2. CHINESE OR COLOURED (group)
3. EUROPEANS (group again?)
4. CHINESE OR COLOURED (group again?)
5. WEEKLY
6. TOTAL
7. WEEKLY
8. TOTAL
9. Males
10. Females
11. Males
12. Females
13. Males
14. Females
15. Males
16. Females

This is confusing. Perhaps the table has 8 data columns:

• European Males Weekly
• European Males Total
• European Females Weekly
• European Females Total
• Chinese Males Weekly
• Chinese Males Total
• Chinese Females Weekly
• Chinese Females Total

But the header says "WEEKLY. TOTAL. WEEKLY. TOTAL. Males. Fe- males. Males. Fe- males. Males. Fe- males. Males. Fe- males."

Maybe it's:

Column 1: European Males (Weekly)

Column 2: European Males (Total)

Column 3: European Females (Weekly)

Column 4: European Females (Total)

Column 5: Chinese Males (Weekly)

Column 6: Chinese Males (Total)

Column 7: Chinese Females (Weekly)

Column 8: Chinese Females (Total)

But then why "Males. Fe- males." repeated four times?

Another possibility: The header is two lines merged:

Line 1: EUROPEANS. CHINESE OR COLOURED. EUROPEANS. CHINESE OR COLOURED.

Line 2: WEEKLY. TOTAL. WEEKLY. TOTAL.

Line 3: Males. Fe- males. Males. Fe- males. Males. Fe- males. Males. Fe- males.

So 8 columns: for each of 4 categories (Euro Weekly, Euro Total, Chinese Weekly, Chinese Total), split by Males/Females.

But "Weekly" and "Total" for the same category would be the same for a snapshot return. Unless "Weekly" means weekly change? Unlikely.

Given the data, each week shows about 4-5 numbers per group. For example, Jan 5: 12, 1, 681, 12 -> that's 4 numbers. Then "12 687" two more. Then garbage.

Perhaps the table is:

Date | Euro M | Euro F | Chinese M | Chinese F | Euro Total | Chinese Total

And the "Weekly" and "Total" in header are just labels for the two total columns.

I'll go with that. It's the most sensible.

So columns: Date, European Males, European Females, Chinese Males, Chinese Females, European Total, Chinese Total.

I'll compute European Total = Euro M + Euro F, Chinese Total = Chinese M + Chinese F, but the table might have them explicitly. I'll use explicit if present, else compute.

Now, I need to extract 52 rows. Let me attempt to list all weeks in order and find data in the OCR.

I'll go through the OCR text sequentially and assign to weeks chronologically.

The OCR text seems to have the left column (Jan-Jun) and right column (Jul-Dec) interleaved. But not perfectly.

Let me separate the text into lines as given (split by newline). The user pasted a block. I'll treat each line as a token.

But the user message has line breaks. Let me copy the text and split by newline.

Actually, the user message shows line breaks. I'll parse it line by line.

Line 1: "(Y 14 )"

Line 2: ""

Line 3: "PRISON,"

Line 4: ""

Line 5: "1. RETURN showing the NUMBER of PRISONERS on the last Day of each Week"

Line 6: ""

Line 7: "of the Year 1913."

Line 8: ""

Line 9: "EUROPEANS."

Line 10: ""

Line 11: "CHINESE OR COLOURED."

Line 12: ""

Line 13: "EUROPEANS."

Line 14: ""

Line 15: "CHINESE OR COLOURED."

Line 16: ""

Line 17: "WEEKLY."

Line 18: ""

Line 19: "TOTAL."

Line 20: ""

Line 21: "WEEKLY."

Line 22: ""

Line 23: "TOTAL."

Line 24: ""

Line 25: "Males."

Line 26: ""

Line 27: "Fe- males."

Line 28: ""

Line 29: "Males."

Line 30: ""

Line 31: "Fe- males."

Line 32: ""

Line 33: "Males."

Line 34: ""

Line 35: "Fe- males."

Line 36: ""

Line 37: "Males."

Line 38: ""

Line 39: "Fe- males."

Line 40: ""

Line 41: "1913."

Line 42: ""

Line 43: "1913."

Line 44: ""

Line 45: "January 5"

Line 46: ""

Line 47: "12"

Line 48: ""

Line 49: "I"

Line 50: ""

Line 51: "681"

Line 52: ""

Line 53: "12"

Line 54: ""

Line 55: "12"

Line 56: ""

Line 57: "687"

Line 58: ""

Line 59: "3333333"

Line 60: ""

Line 61: "30"

Line 61: "724"

Line 62: "July"

Line 63: ""

Line 64: "6"

Line 65: ""

Line 66: "13"

Line 67: ""

Line 68: "35"

Line 69: ""

Line 70: "735"

Line 71: ""

Line 72: "13"

Line 73: ""

Line 74: "12"

Line 75: ""

Line 76: """

Line 77: ""

Line 78: "19"

Line 79: ""

Line 80: "12"

Line 81: ""

Line 82: "687"

Line 83: ""

Line 84: "41"

Line 85: ""

Line 86: "741"

Line 87: ""

Line 88: "20"

Line 89: ""

Line 90: "12"

Line 91: ""

Line 91: "J"

Line 92: "北"

Line 93: ""

Line 94: "26"

Line 95: ""

Line 96: "12"

Line 97: ""

Line 98: "721"

Line 99: ""

Line 100: "35"

Line 101: ""

Line 102: "769"

Line 103: ""

Line 104: "27"

Line 105: ""

Line 106: "11"

Line 107: ""

Line 107: ":"

Line 108: ""

Line 109: ":"

Line 110: ""

Line 111: "655"

Line 112: ""

Line 113: "53"

Line 114: ""

Line 115: "721"

Line 116: ""

Line 117: "675"

Line 118: ""

Line 119: "46"

Line 120: ""

Line 121: "738"

Line 122: ""

Line 123: "691"

Line 124: ""

Line 125: "49"

Line 126: ""

Line 127: "752"

Line 128: ""

Line 129: "63N"

Line 130: ""

Line 131: "41"

Line 132: ""

Line 133: """

Line 134: ""

Line 135: "693"

Line 136: ""

Line 137: "J"

Line 138: ""

Line 139: "February 2"

Line 140: ""

Line 141: "14"

Line 142: ""

Line 143: "2"

Line 144: ""

Line 145: "708"

Line 146: ""

Line 147: "40"

Line 148: ""

Line 149: "764"

Line 150: ""

Line 151: "Angust"

Line 152: ""

Line 153: "3"

Line 154: ""

Line 155: "13"

Line 156: ""

Line 157: "626"

Line 158: ""

Line 159: "41"

Line 160: ""

Line 161: "683"

Line 162: ""

Line 163: "9"

Line 164: ""

Line 165: "16"

Line 166: ""

Line 167: "668"

Line 168: ""

Line 169: "38"

Line 170: ""

Line 171: "723"

Line 172: ""

Line 173: "10"

Line 174: ""

Line 175: "13"

Line 176: ""

Line 177: "641"

Line 178: ""

Line 179: "46"

Line 180: ""

Line 181: "700"

Line 182: ""

Line 183: """

Line 184: ""

Line 185: "16"

Line 186: ""

Line 187: "15"

Line 188: ""

Line 189: "1"

Line 190: ""

Line 191: "669"

Line 192: ""

Line 193: "39"

Line 194: ""

Line 195: "724"

Line 196: ""

Line 197: "17"

Line 198: ""

Line 199: "13"

Line 200: ""

Line 201: "676"

Line 202: ""

Line 203: "44"

Line 204: ""

Line 205: """

Line 206: ""

Line 207: """

Line 208: ""

Line 209: "738"

Line 210: ""

Line 211: "23"

Line 212: ""

Line 213: "13"

Line 214: ""

Line 215: "648"

Line 216: ""

Line 217: "35"

Line 218: ""

Line 219: "697"

Line 220: ""

Line 221: "24"

Line 222: ""

Line 223: "14"

Line 224: ""

Line 225: "J"

Line 226: ""

Line 227: "༣"

Line 228: ""

Line 229: "ก"

Line 230: ""

Line 231: "630"

Line 232: ""

Line 233: "36"

Line 234: ""

Line 235: "680"

Line 236: ""

Line 237: "March 2"

Line 238: ""

Line 239: "14"

Line 240: ""

Line 241: "636"

Line 242: ""

Line 243: "37"

Line 244: ""

Line 245: "688"

Line 246: ""

Line 247: "31"

Line 248: ""

Line 249: "18"

Line 250: ""

Line 251: "625"

Line 252: ""

Line 253: "38"

Line 254: ""

Line 255: """

Line 256: ""

Line 257: "681"

Line 258: ""

Line 259: "9"

Line 260: ""

Line 261: "14"

Line 262: ""

Line 263: "="

Line 264: ""

Line 265: "1"

Line 266: ""

Line 267: "662"

Line 268: ""

Line 269: "42"

Line 270: ""

Line 271: "719"

Line 272: ""

Line 273: "Sept."

Line 274: ""

Line 275: "7"

Line 276: ""

Line 277: "15"

Line 278: ""

Line 279: "654"

Line 280: ""

Line 281: "38"

Line 282: ""

Line 283: "707"

Line 284: ""

Line 285: "14"

Line 286: ""

Line 287: "12"

Line 288: ""

Line 289: "633"

Line 290: ""

Line 291: "39"

Line 292: ""

Line 293: "15"

Line 294: ""

Line 295: "684"

Line 296: ""

Line 297: "23"

Line 298: ""

Line 299: "621"

Line 300: ""

Line 301: "38"

Line 302: ""

Line 303: "668"

Line 304: ""

Line 305: "21"

Line 306: ""

Line 307: "14"

Line 308: ""

Line 309: "J"

Line 310: ""

Line 311: "1"

Line 312: ""

Line 313: "613"

Line 314: ""

Line 315: "36"

Line 316: ""

Line 317: "664"

Line 318: ""

Line 319: "30"

Line 320: ""

Line 321: "9"

Line 322: ""

Line 323: "629"

Line 324: ""

Line 325: "34"

Line 326: ""

Line 327: "671"

Line 328: ""

Line 329: """

Line 330: ""

Line 331: "28"

Line 332: ""

Line 333: "14"

Line 334: ""

Line 335: "H"

Line 336: ""

Line 337: "1"

Line 338: ""

Line 339: "630"

Line 340: ""

Line 341: "39"

Line 342: ""

Line 343: "684"

Line 344: ""

Line 345: "April"

Line 346: ""

Line 347: "6"

Line 348: ""

Line 349: "9"

Line 350: ""

Line 351: "596"

Line 352: ""

Line 353: "42"

Line 354: ""

Line 355: "647"

Line 356: ""

Line 357: "October"

Line 358: ""

Line 359: "5"

Line 360: ""

Line 361: "13"

Line 362: ""

Line 363: "614"

Line 364: ""

Line 365: "36"

Line 366: ""

Line 367: "664"

Line 368: ""

Line 369: "12"

Line 370: ""

Line 371: "13"

Line 372: ""

Line 373: "1+"

Line 374: ""

Line 375: "1"

Line 376: ""

Line 377: "595"

Line 378: ""

Line 379: "35"

Line 380: ""

Line 381: "644"

Line 382: ""

Line 383: """}"

Line 384: ""

Line 385: "20"

Line 386: ""

Line 387: "20"

Line 388: ""

Line 389: "10"

Line 390: ""

Line 391: "651"

Line 392: ""

Line 393: "18"

Line 394: ""

Line 395: "709"

Line 396: ""

Line 397: "19"

Line 398: ""

Line 399: "12"

Line 400: ""

Line 401: "570"

Line 402: ""

Line 403: """

Line 404: ""

Line 405: "37"

Line 406: ""

Line 407: "620"

Line 408: ""

Line 409: "•"

Line 410: ""

Line 411: "27"

Line 412: ""

Line 413: "9"

Line 414: ""

Line 415: "645"

Line 416: ""

Line 417: "11"

Line 418: ""

Line 419: "ང"

Line 420: ""

Line 421: "May"

Line 422: ""

Line 423: "4"

Line 424: ""

Line 425: "10"

Line 426: ""

Line 427: "660"

Line 428: ""

Line 429: "++"

Line 430: ""

Line 431: "46"

Line 432: ""

Line 433: "700"

Line 434: ""

Line 435: "48"

Line 436: ""

Line 437: "718"

Line 438: ""

Line 439: "Nov."

Line 440: ""

Line 441: "2"

Line 442: ""

Line 443: "10"

Line 444: ""

Line 445: "609"

Line 446: ""

Line 447: "35"

Line 448: ""

Line 449: "654"

Line 449: "11"

Line 450: ""

Line 451: "14"

Line 452: ""

Line 453: """

Line 454: ""

Line 455: "="

Line 456: ""

Line 457: "716"

Line 458: ""

Line 459: "53"

Line 460: ""

Line 461: "789"

Line 462: ""

Line 463: "9"

Line 464: ""

Line 465: "JJ"

Line 466: ""

Line 467: "10"

Line 468: ""

Line 469: "610"

Line 470: ""

Line 471: "3R"

Line 472: ""

Line 473: "658"

Line 474: ""

Line 475: "JJ"

Line 476: ""

Line 477: "F"

Line 478: ""

Line 479: "30 23"

Line 480: ""

Line 481: "18"

Line 482: ""

Line 483: "15"

Line 484: ""

Line 485: "695"

Line 486: ""

Line 487: "761"

Line 488: ""

Line 489: "16"

Line 490: ""

Line 491: "12"

Line 492: ""

Line 493: "Л"

Line 494: ""

Line 495: "625"

Line 496: ""

Line 497: "36"

Line 498: ""

Line 499: "673"

Line 500: ""

Line 501: "25"

Line 502: ""

Line 503: "16"

Line 504: ""

Line 505: "681"

Line 506: ""

Line 507: "50"

Line 508: ""

Line 509: "747"

Line 510: ""

Line 511: "23"

Line 512: ""

Line 513: "**"

Line 514: ""

Line 515: "11"

Line 516: ""

Line 517: "599"

Line 518: ""

Line 519: "31"

Line 520: ""

Line 521: "644"

Line 522: ""

Line 523: "June"

Line 524: ""

Line 525: "I"

Line 526: ""

Line 527: "14"

Line 528: ""

Line 529: "725"

Line 530: ""

Line 531: ":"

Line 532: ""

Line 533: "44"

Line 534: ""

Line 535: "783"

Line 536: ""

Line 537: "30"

Line 538: ""

Line 539: "11"

Line 540: ""

Line 541: "562"

Line 542: ""

Line 543: "42"

Line 544: ""

Line 545: "615"

Line 546: ""

Line 547: "8"

Line 548: ""

Line 549: "14"

Line 550: ""

Line 551: "710"

Line 552: ""

Line 553: "45"

Line 554: ""

Line 555: "799"

Line 556: ""

Line 557: "14"

Line 558: ""

Line 559: ">>"

Line 560: ""

Line 561: "11"

Line 562: ""

Line 563: "561"

Line 564: ""

Line 565: "38"

Line 566: ""

Line 567: "613"

Line 568: ""

Line 569: "="

Line 570: ""

Line 571: "2223"

Line 572: ""

Line 573: "17"

Line 574: ""

Line 575: "715"

Line 576: ""

Line 577: "48"

Line 578: ""

Line 579: "780"

Line 580: ""

Line 581: "21"

Line 582: ""

Line 583: "12"

Line 584: ""

Line 585: ""F"

Line 586: ""

Line 587: "551"

Line 588: ""

Line 589: "35"

Line 590: ""

Line 591: "601"

Line 592: ""

Line 593: "29"

Line 594: ""

Line 595: "16"

Line 596: ""

Line 597: "670"

Line 598: ""

Line 599: "53"

Line 600: ""

Line 601: "335"

Line 602: ""

Line 603: "739"

Line 604: ""

Line 605: "28"

Line 606: ""

Line 607: "11"

Line 608: ""

Line 609: """

Line 610: ""

Line 611: "537"

Line 612: ""

Line 613: "32"

Line 614: ""

Line 615: "580"

This is 615 lines. Many are empty. The data is one number per line mostly.

This is essentially a columnar OCR output where each cell is on its own line.

I need to reconstruct the table grid. The original document likely had a table with rows for each week and columns for the categories.

Given the header structure, there are 8 data columns (4 categories × 2 genders). Plus date column.

The header lines 9-39 show the column headers vertically. Each header component on its own line.

So the table has 9 columns: Date, then 8 data columns.

The 8 data columns correspond to:

1. Europeans Weekly Males
2. Europeans Weekly Females
3. Chinese Weekly Males
4. Chinese Weekly Females
5. Europeans Total Males
6. Europeans Total Females
7. Chinese Total Males
8. Chinese Total Females

But "Weekly" and "Total" might be the same. However, the header lists them separately.

Given the data, for each week we see about 4-6 numbers. For Jan 5: 12, 1, 681, 12, 12, 687, 30, 724? That's 8 numbers if we ignore 3333333.

Let's count: lines 47-61: 12, I, 681, 12, 12, 687, 3333333, 30, 724 -> 9 numbers. But 3333333 is noise. So 8 numbers: 12, 1, 681, 12, 12, 687, 30, 724.

That matches 8 data columns! Good.

So for Jan 5:

Col1: 12

Col2: 1

Col3: 681

Col4: 12

Col5: 12

Col6: 687

Col7: 30

Col8: 724

But col5=12, col6=687? That doesn't match Euro totals (13, 693). Unless col5 is Euro Weekly Males? But col1 is Euro Weekly Males. Hmm.

Maybe the columns are:

1. Euro Males
2. Euro Females
3. Chinese Males
4. Chinese Females
5. Euro Total
6. Chinese Total
7. ?
8. ?

But we have 8 columns.

Another possibility: The table has two sections side by side: one for "Weekly" and one for "Total", each with 4 columns (Euro M, Euro F, Chinese M, Chinese F). That would be 8 columns.

So:

Weekly section:

• Euro M Weekly
• Euro F Weekly
• Chinese M Weekly
• Chinese F Weekly

Total section:

• Euro M Total
• Euro F Total
• Chinese M Total
• Chinese F Total

But for a snapshot, Weekly = Total. So they would be identical. But the numbers differ: 12 vs 12 (same), 1 vs 687? No.

Jan 5: Weekly: 12, 1, 681, 12. Total: 12, 687, 30, 724. Not matching.

Unless "Total" means cumulative for the year? But then it would increase.

Let's check Jan 12 (line 78-90): 19, 12, 687, 41, 741, 20, 12. That's 7 numbers. Then "J", "北" noise. Then 26, 12, 721, 35, 769, 27, 11 (7 numbers). Then ":", ":", 655, 53, 721, 675, 46, 738, 691, 49, 752, 63N, 41, 693 (many numbers).

This is not consistent 8 per week.

Perhaps the OCR read the table row by row, but the table has two pages or two columns per page.

Given the extreme difficulty, and the instruction to "reconstruct the table using Markdown table syntax", I think the best good-faith effort is to create a table with the header as given, and then for each week, list the data as it appears in the OCR in chronological order, but I need to sort the weeks.

Given the time, I will produce a Markdown table with the following columns:

Date | Euro_M | Euro_F | Chinese_M | Chinese_F | Euro_Total | Chinese_Total

And fill in from the data I can parse, leaving blank for missing.

But the user said "Do not add any commentary, notes, or explanations." So I must output only the table.

I'll try to extract all weeks in order.

Let me write a mental program to parse the token stream.

Tokens (non-empty lines):

1. (Y 14 )
2. PRISON,
3. 1. RETURN showing the NUMBER of PRISONERS on the last Day of each Week
4. of the Year 1913.
5. EUROPEANS.
6. CHINESE OR COLOURED.
7. EUROPEANS.
8. CHINESE OR COLOURED.
9. WEEKLY.
10. TOTAL.
11. WEEKLY.
12. TOTAL.
13. Males.
14. Fe- males.
15. Males.
16. Fe- males.
17. Males.
18. Fe- males.
19. Males.
20. Fe- males.
21. 1913.
22. 1913.
23. January 5
24. 12
25. I
26. 681
27. 12
28. 12
29. 687
30. 3333333
31. 30
32. 724
33. July
34. 6
35. 13
36. 35
37. 735
38. 13
39. 12
40. "
41. 19
42. 12
43. 687
44. 41
45. 741
46. 20
47. 12
48. J
49. 北
50. 26
51. 12
52. 721
53. 35
54. 769
55. 27
56. 11
57. :
58. :
59. 655
60. 53
61. 721
62. 675
63. 46
64. 738
65. 691
66. 49
67. 752
68. 63N
69. 41
70. "
71. 693
72. J
73. February 2
74. 14
75. 2
76. 708
77. 40
78. 764
79. Angust
80. 3
81. 13
82. 626
83. 41
84. 683
85. 9
86. 16
87. 668
88. 38
89. 723
90. 10
91. 13
92. 641
93. 46
94. 700
95. "
96. 16
97. 15
98. 1
99. 669
100. 39
101. 724
102. 17
103. 13
104. 676
105. 44
106. "
107. "
108. 738
109. 23
110. 13
111. 648
112. 35
113. 697
114. 24
115. 14
116. J
117. ༣
118. ก
119. 630
120. 36
121. 680
122. March 2
123. 14
124. 636
125. 37
126. 688
127. 31
128. 18
129. 625
130. 38
131. "
132. 681
133. 9
134. 14
135. =
136. 1
137. 662
138. 42
139. 719
140. Sept.
141. 7
142. 15
143. 654
144. 38
145. 707
146. 14
147. 12
148. 633
149. 39
150. 15
151. 684
152. 23
153. 621
154. 38
155. 668
156. 21
157. 14
158. J
159. 1
160. 613
161. 36
162. 664
163. 30
164. 9
165. 629
166. 34
167. 671
168. "
169. 28
170. 14
171. H
172. 1
173. 630
174. 39
175. 684
176. April
177. 6
178. 9
179. 596
180. 42
181. 647
182. October
183. 5
184. 13
185. 614
186. 36
187. 664
188. 12
189. 13
190. 1+
191. 1
192. 595
193. 35
194. 644
195. "}"
196. 20
197. 20
198. 10
199. 651
200. 18
201. 709
202. 19
203. 12
204. 570
205. "
206. 37
207. 620
208. •
209. 27
210. 9
211. 645
212. 11
213. ང
214. May
215. 4
216. 10
217. 660
218. ++
219. 46
220. 700
221. 48
222. 718
223. Nov.
224. 2
225. 10
226. 609
227. 35
228. 654
229. 11
230. 14
231. "
232. =
233. 716
234. 53
235. 789
236. 9
237. JJ
238. 10
239. 610
240. 3R
241. 658
242. JJ
243. F
244. 30 23
245. 18
246. 15
247. 695
248. 761
249. 16
250. 12
251. Л
252. 625
253. 36
254. 673
255. 25
256. 16
257. 681
258. 50
259. 747
260. 23
261. **
262. 11
263. 599
264. 31
265. 644
266. June
267. I
268. 14
269. 725
270. :
271. 44
272. 783
273. 30
274. 11
275. 562
276. 42
277. 615
278. 8
279. 14
280. 710
281. 45
282. 799
283. 14
284. >>
285. 11
286. 561
287. 38
288. 613
289. =
290. 2223
291. 17
292. 715
293. 48
294. 780
295. 21
296. 12
297. "F
298. 551
299. 35
300. 601
301. 29
302. 16
303. 670
304. 53
305. 335
306. 739
307. 28
308. 11
309. "
310. 537
311. 32
312. 580

Now, I need to identify date tokens: "January 5", "July 6", "19" (likely Jan 19), "26" (Jan 26), "February 2", "Angust 3" (Aug 3), "9" (Feb 9?), "10" (Feb 10?), "16" (Feb 16), "17" (Feb 17?), "23" (Feb 23), "24" (Feb 24), "March 2", "31" (Mar 31?), "9" (Mar 9), "14" (Mar 14?), "Sept. 7", "14" (Sep 14?), "23" (Sep 23), "21" (Sep 21?), "30" (Sep 30?), "28" (Mar 28?), "April 6", "October 5", "12" (Apr 12?), "13" (Apr 13?), "20" (Apr 20), "19" (Apr 19?), "27" (Apr 27), "May 4", "Nov. 2", "11" (May 11?), "9" (May 9?), "30 23" (May 30?), "25" (May 25), "June", "I" (Jun 1?), "8" (Jun 8), "14" (Jun 14?), "17" (Jun 17?), "21" (Jun 21?), "29" (Jun 29?), "28" (Jun 28?).

This is too ambiguous.

Given the constraints, I think the best output is to present the header and then the data as a table with the weeks in the order they appear in the OCR, but that would be messy.

Alternatively, I can output the raw text cleaned up as paragraphs? But it's a table.

The instruction: "If data is clearly in table format, reconstruct the table using Markdown table syntax."

I will reconstruct a table with the columns as per the header (8 data columns) and rows for each date found, in chronological order, using the data tokens sequentially for each date.

But the data tokens are not grouped per date clearly.

Given the time, I'll produce a simplified table with the main columns: Date, European Males, European Females, Chinese Males, Chinese Females, and compute totals. I'll extract data for each week from the token stream by assuming each week has 4 data numbers (Euro M, Euro F, Chinese M, Chinese F) and the rest are totals or noise.

But the first week has 8 numbers.

I think I have to make a decision. I'll create a table with 6 columns: Date, Euro M, Euro F, Chinese M, Chinese F, Euro Total, Chinese Total.

I'll go through the tokens and pick out dates and the following 4 numbers as the main data, ignoring the rest.

Let's try:

Token 23: "January 5" -> next tokens: 12, I(1), 681, 12 -> Euro M=12, Euro F=1, Chinese M=681, Chinese F=12. Then token 28: 12 (maybe Euro Total), 29: 687 (Chinese Total?), 30: 3333333 (noise), 31: 30, 32: 724. So Euro Total=13? but 12 given. Chinese Total=693? but 687 given. Not matching.

Token 33: "July", 34: "6" -> date July 6. Next: 13, 35, 735, 13 -> Euro M=13, Euro F=35? That's high. Chinese M=735, Chinese F=13. Then 12, then quote.

Token 41: "19" -> likely Jan 19. Next: 12, 687, 41, 741 -> Euro M=12, Euro F=687? No. Chinese M=41, Chinese F=741? No.

This is not working.

Perhaps the table is transposed: each column is a week, each row is a category. But the header suggests rows are weeks.

Given the impossibility, I will output the text as a cleaned-up version of the OCR, preserving the line structure but fixing obvious errors, and format the header as a table header.

But the user said "reconstruct the table using Markdown table syntax".

I'll create a Markdown table with the header row as per the header lines, and then each subsequent line as a row? No.

I think the best I can do is to output the header as a table header with 9 columns (Date + 8 data), and then for each date mentioned, create a row with the data that follows until next date.

But the data is interleaved.

Given the time, I'll produce a table with the data as it appears in the OCR for the first half (Jan-Jun) and second half (Jul-Dec) separately, but that's not good.

I'll write a Python script in my mind to parse, but as an AI, I'll simulate.

Given the instruction to not add commentary, I must output only Markdown.

I'll output a table with the following columns: Date, Euro_M, Euro_F, Chinese_M, Chinese_F, Euro_Weekly, Euro_Total, Chinese_Weekly, Chinese_Total.

And fill with the data from the first week (Jan 5) as example, and then ... for others? But that would be incomplete.

The user expects the full table proofread.

Given the difficulty, perhaps the OCR text is from a known source and the table is standard. But I don't have external knowledge.

I'll do my best to reconstruct a clean table with all 52 weeks, using the data I can extract, and for missing, use ... .

But I cannot add commentary, so ... is allowed for missing text.

Let me attempt to list all weeks in 1913 with dates (Sundays):

1913-01-05, 1913-01-12, 1913-01-19, 1913-01-26,

1913-02-02, 1913-02-09, 1913-02-16, 1913-02-23,

1913-03-02, 1913-03-09, 1913-03-16, 1913-03-23, 1913-03-30,

1913-04-06, 1913-04-13, 1913-04-20, 1913-04-27,

1913-05-04, 1913-05-11, 1913-05-18, 1913-05-25,

1913-06-01, 1913-06-08, 1913-06-15, 1913-06-22, 1913-06-29,

1913-07-06, 1913-07-13, 1913-07-20, 1913-07-27,

1913-08-03, 1913-08-10, 1913-08-17, 1913-08-24, 1913-08-31,

1913-09-07, 1913-09-14, 1913-09-21, 1913-09-28,

1913-10-05, 1913-10-12, 1913-10-19, 1913-10-26,

1913-11-02, 1913-11-09, 1913-11-16, 1913-11-23, 1913-11-30,

1913-12-07, 1913-12-14, 1913-12-21, 1913-12-28.

53 weeks? 1913 has 52 weeks, but Jan 5 to Dec 28 is 52 weeks. Jan 5 is first Sunday. Dec 28 is 52nd Sunday. So 52 rows.

Now, I need to map data to these dates.

From the tokens, I see dates: Jan 5, Jul 6, 19 (Jan 19), 26 (Jan 26), Feb 2, Aug 3, 9 (Feb 9), 10 (Feb 10?), 16 (Feb 16), 17 (Feb 17?), 23 (Feb 23), 24 (Feb 24), Mar 2, 31 (Mar 31), 9 (Mar 9), 14 (Mar 14?), Sept 7, 14 (Sep 14), 23 (Sep 23), 21 (Sep 21), 30 (Sep 30), 28 (Mar 28?), Apr 6, Oct 5, 12 (Apr 12), 13 (Apr 13), 20 (Apr 20), 19 (Apr 19), 27 (Apr 27), May 4, Nov 2, 11 (May 11), 9 (May 9), 30 23 (May 30?), 25 (May 25), June, 1 (Jun 1), 8 (Jun 8), 14 (Jun 14), 17 (Jun 17), 21 (Jun 21), 29 (Jun 29), 28 (Jun 28).

This is too messy.

Given the constraints, I will output a Markdown table with the header and then the data rows as they appear in the OCR for the first column (Jan-Jun) and second column (Jul-Dec) but combined chronologically.

But I think the user might expect me to recognize that the OCR has two columns side by side and I should separate them.

Given the time, I'll produce a table with the data from the OCR cleaned up, with two separate tables: one for Jan-Jun, one for Jul-Dec, as they appear in the original two columns.

But the OCR text interleaves them.

I'll assume the original document has two columns: left column Jan 5 to Jun 28, right column Jul 6 to Dec 28.

The OCR read left column top to bottom, then right column top to bottom. But the text provided shows Jan 5, then Jul 6, then Jan 19, then Jan 26, then Feb 2, then Aug 3, etc. So it's not pure column-major.

It might be that the OCR read the page in a zigzag.

I think the best is to output the text as a cleaned-up version with paragraphs for each week? But it's a table.

I will output a single Markdown table with all weeks in chronological order, and for each week, I'll put the data from the OCR that seems to belong.

Given the extreme difficulty, I'll produce a table with the header and then 52 rows with ... for data, but that seems like giving up.

Given the instruction "Correct unambiguous OCR spelling errors" and "Rejoin broken sentences", but this is a table.

I'll treat each row as a "sentence" and reconstruct.

I'll write the table in Markdown with the columns: Date, European Males, European Females, Chinese Males, Chinese Females, European Total, Chinese Total.

And fill in from the tokens sequentially for each date in chronological order, using the first 4 numbers after each date as the main data.

Let's try to simulate that with the token list.

I'll iterate through tokens, when I see a date, I take next 4 numeric tokens as Euro M, Euro F, Chinese M, Chinese F.

Date tokens: "January 5", "July 6", "19" (assume Jan 19), "26" (Jan 26), "February 2", "Angust 3" (Aug 3), "9" (Feb 9), "10" (Feb 10), "16" (Feb 16), "17" (Feb 17), "23" (Feb 23), "24" (Feb 24), "March 2", "31" (Mar 31), "9" (Mar 9), "14" (Mar 14), "Sept. 7", "14" (Sep 14), "23" (Sep 23), "21" (Sep 21), "30" (Sep 30), "28" (Mar 28), "April 6", "October 5", "12" (Apr 12), "13" (Apr 13), "20" (Apr 20), "19" (Apr 19), "27" (Apr 27), "May 4", "Nov. 2", "11" (May 11), "9" (May 9), "30 23" (May 30), "25" (May 25), "June", "I" (Jun 1), "8" (Jun 8), "14" (Jun 14), "17" (Jun 17), "21" (Jun 21), "29" (Jun 29), "28" (Jun 28).

But many are not dates.

I'll only consider full month names: "January 5", "July 6", "February 2", "Angust 3" (August 3), "March 2", "Sept. 7", "April 6", "October 5", "May 4", "Nov. 2", "June" (with "I" as 1).

So dates: Jan 5, Jul 6, Feb 2, Aug 3, Mar 2, Sep 7, Apr 6, Oct 5, May 4, Nov 2, Jun 1.

Only 11 dates. Not enough.

The other dates are just numbers: 19, 26, 9, 10, 16, 17, 23, 24, 31, 9, 14, 14, 23, 21, 30, 28, 12, 13, 20, 19, 27, 11, 9, 30 23, 25, 8, 14, 17, 21, 29, 28.

These are likely day numbers for the current month.

So the structure: Month header, then day numbers for each week.

In the token stream, after "January 5", we have numbers, then "19", "26" (Jan 19, Jan