The user wants me to proofread OCR output of a historical document - specifically a "LIST OF OFFICERS" index/table of contents. The OCR has many errors: broken words, misread characters, wrong spacing, etc. I need to reconstruct this as a clean Markdown table.

Looking at the structure: It appears to be a three-column table (OFFICE, PAGE, OFFICE, PAGE, OFFICE, PAGE) but actually it's listing names with page numbers. The header shows "OFFICE PAGE" repeated three times, suggesting three columns of names and page numbers.

The content is a list of officers with their names and page numbers. I need to parse this into a proper table.

Let me analyze the data. It seems like each row has three entries: Name, Page, Name, Page, Name, Page. But the OCR has messed up the alignment.

I'll reconstruct as a Markdown table with columns: Name, Page, Name, Page, Name, Page. But actually, looking at the header: "OFFICE PAGE OFFICE PAGE OFFICE PAGE" - so it's three pairs of columns.

But the data seems to be just names and page numbers. "OFFICE" might be a misnomer - it's actually "NAME" or "OFFICER". But I'll keep the header as given.

Let me parse the data line by line. The OCR text is messy. I'll try to group into rows.

First, after the header, there's "J J J" - probably column separators or something.

Then "L-Continued. L-Continued. L—Continued." - indicating this is continuation of L section.

Then names start: "Lai-Poon, C. 21 Lambert, E. B. 120 Lay, T. 15" - that's three entries.

Next line: "Lai Pui-kon 13 Lambert, W. 0. 80 Layne, D. 07" - but "W. 0." likely "W. O." or "W.0."? Probably "W. O.".

"Ini Shiu-tso 08" - "Ini" likely "Lai" or something? Actually "Lai Shiu-tso"? But previous was "Lai Pui-kon". Could be "Lai Shiu-tso". But OCR says "Ini". Might be "Lai Shiu-tso". I'll keep as "Lai Shiu-tso" with note? But rule: correct unambiguous OCR errors. "Ini" -> "Lai" is plausible. But I'll keep as "Lai Shiu-tso" assuming it's a continuation of Lai names.

"Laшprill, W. C. R.... 82" - "Laшprill" likely "Lamprill" or "Lamprill"? Actually "Lamprill, W. C. R.".

"Lee, A. W. G8" - "G8" likely "68".

"Lai Tze-inAN 121" - "inAN" likely "in An" or "in An"? Probably "Lai Tze-in An" or "Lai Tze-inan"? But page 121.

"Lane, L. P. 49 Lee Chuen 125"

"Lai Yau 124, 126 Lang. E. P. H, 42 Lee Chung-wen 69"

"Lai Yau-kit 28 Lang, J. C. 11 Lee, E. 59"

"Lai Yau-yick 110 Langley, R. 96 Lee Ek-leong 6.3" -> "6.3" likely "63".

"Lai Yew-ming 10 Lau, A. 62 Lee Fook 120"

"Lai Ying 18 Lau Che-wa 19 Lec, J. 120" -> "Lec" likely "Lee, J." but already have Lee, J. H. B. later. Could be "Lee, J.".

"Lai Yuen-ping 122 Lau Cheong B" -> "B" likely "8" or "18"? But page B? Might be "8". But "Lau Cheong 8"? However "Lau Cheong" appears later? Actually "Lau Cheong B" - maybe "Lau Cheong 8". But "B" could be "8" misread.

"Lee, J. H. B. 1, 3, 4"

"Lakeman, J. 62 Lau Cheuk-nam 18 ." -> extra dot.

"Lee Kam-ming 10"

"Lain Chak-shing 48 Lau Cheung 108 Lee Kew 118" -> "Lain" likely "Lam Chak-shing"? But "Lam" names earlier. Could be "Lam Chak-shing". But "Lain" might be "Lam". I'll correct to "Lam Chak-shing".

"Lam Cheuk-but 02 Lau Chuch 121 Lee King-shum 101" -> "02" likely "102"? But "Lam Cheuk-but 102"? "Lau Chuch" likely "Lau Chuk" or "Lau Chuch"? Probably "Lau Chuk".

"Lam Chew 125 Lau Chuen-huen 16 Lee, M. E. 07" -> "07" likely "57"? But "Lee, M. E. 57"? Later "Lee, M. E. 07" maybe "57".

"Lan Chifung В Lau Chuen-ki 10 Lee Maü-lin 122" -> "В" is Cyrillic? Likely "8" or "B". "Lan Chifung 8"? But "Lam Chifung"? Actually "Lam Chi-fung"? "Lan Chifung" maybe "Lam Chi-fung". "В" -> "8".

"Lam Chi-wie 71 Lau Chui 102 Lee Mun-fong 103"

"Lam Chuen 19 Lau Chung-bin 85 Lee Nai-tong 120"

"Lam Chun 125 Lau Chung-pun 90 Lee Po-tin 70"

"Lam Chun-hi 21 Lau Fook-tseung 18 | Lee Pui-sum 21" -> pipe is artifact.

"Lam Fai 21 Lau For-lam 6 Lee Shu-sun 44"

"Lam Heung-wing 105 Lnu Fuk 100 Lee Suey-wing 86" -> "Lnu" likely "Lau Fuk".

"Lam Hon-cheong 105 Lau ilin. 106 Lee Tack-hing 69" -> "ilin." likely "Lin" or "Lui"? "Lau Lin"? But "Lau Lin 106"? Could be "Lau Lin".

"Lam Hung-ki 103 Lau flo-chuen 85 Lee Tsan-chiu 27" -> "flo-chuen" likely "Fook-chuen" or "Flo-chuen"? Probably "Lau Fook-chuen".

"Lam Iu-bun 6 Lau Hong 117 Lee Yau-yuD 12" -> "yuD" likely "yun".

"Lam. J. 93 Lau Ip-yuen 8+ Lee Yo-wing 10" -> "8+" likely "81" or "84"? "8+" maybe "81".

"Lain Kai 19 Lau Kam-yung 16 Lee Yuk-him 75" -> "Lain Kai" likely "Lam Kai".

"Lam Kai-tseung 39 Lau Kan 105 Lei Peng-ü 78" -> "Lei Peng-ü" maybe "Lee Peng-ü"? But "Lei" could be "Lee". But keep as "Lei Peng-ü".

"Lam Karo 125 Lau King-ming 89 Lenaghan, J. 65"

"Lam Kin-tong 120 Lau Ku 118 Leufestev, F. P. 28" -> "Leufestev" likely "Leufestev"? Maybe "Leufestev" is "Leufestev"? Could be "Leufestev" but probably "Leufestev" is a name. Might be "Leufestev" -> "Leufestev"? I'll keep as "Leufestev, F. P.".

"Lam King-shang 127 Lau Kun 87 Lenz, M. G. 17, 18"

"Lani King-yuen 94 Lau Kwai, D. 123 Leo, K. 57" -> "Lani" likely "Lam King-yuen". "Lau Kwai, D." maybe "Lau Kwai, D.".

"Lou Kwan 40 Lan Kwoh-u 68. 71 Leong Yuen-lok 73" -> "Lou Kwan" maybe "Lau Kwan"? But "Lou" could be "Lau". "Lan Kwoh-u" likely "Lam Kwoh-u". "Leong Yuen-lok".

"Lam Leung 87 Lau Lai-san 78 Leung Biu-ling 116"

"Lam Ling Lain, M. 16 Lau Lai-shang 68 Lau Lok 97 Leung Cheuk-ü 93" -> This line has four entries? Actually "Lam Ling" (no page), "Lain, M. 16", "Lau Lai-shang 68", "Lau Lok 97", "Leung Cheuk-ü 93". That's five entries. But table is three columns. Might be misaligned.

"106 Leung Cheung 122" -> "106" likely page for previous? "Lam Ling 106"? But "Lam Ling" no page. Then "Leung Cheung 122".

"Lam Ming 24 Lau Man 118 Leung Chik-wai 116"

"Lam Pak 25 Lau Man-kui 98 Leung Ching-yu 45"

"Lam Pak-to 101 L. On 148 Leung Chiu-tung 86" -> "L. On" maybe "Lau On"? But "L. On 148".

"Lam Ping-ki 105 Lau Pak-wah 39 Leung Choi 106"

"Lam Poi 125 Lau Ping 106 Leung Chuk-hin 13"

"Lam Pai 25 Jau Sam 118 Leung Chung-kan 60.84" -> "Jau Sam" likely "Lau Sam"? But "Jau" maybe "Lau". "Leung Chung-kan 60.84" -> "60.84" likely "60, 84" or "60-84".

"Lam Shai-tit 127 Lam Sher-song 21 Lau Shiu Lau Shiu-chung 108 Leung Chung-yin 105" -> "Lam Sher-song" maybe "Lam Shek-song"? "Lau Shiu Lau Shiu-chung" duplicated.

"6 Leung, F. 56" -> "6" maybe page for previous? "Leung Chung-yin 105 6"? No.

"Lam Shiu-chi 73, 74 Lau Shuk-chong 8.91 Leung Fan 105" -> "8.91" likely "89, 91"? Or "891"? Probably "89, 91".

"Lam Shiu-fong Lam Shiu-huen 73 Lau Shuk-ying 99 Leung Fat 125" -> two Lam entries.

"21 Lau Sik-hung 20 Leung Fong 108" -> "21" maybe page for previous? "Lam Shiu-huen 73 21"? No.

"Lan. Shiu-kwong 74 Lau Tak-cheuk 98 Leung Foo 17"

"Lam Shiu-wa Lam Chu-tung 100 Lau Tin-chak 101 Leung Fung-ki 97"

"28. 87 Lau Ting-tui 123 Leung Gon-ting 69" -> "28. 87" maybe pages for "Lam Shiu-wa"? But "Lam Shiu-wa" no page. "Lam Chu-tung 100". "28. 87" could be "28, 87" for "Lam Shiu-wa"? But unclear.

"Lam Shui-paug 26, 110 Lau Tsz-ping 8 Leung He-man 74"

"Lan. Sik 21 Lau. V. L. BO Leung Hei 27" -> "BO" likely "80"? "Lau. V. L. 80".

"Lam Sing-U 17 Lau Wing-hon 20 Leung Hi-cheong 116"

"Lain Tin 14 Lau Wing-kwong 62 Leung Hin-cheong 117"

"Lam Tsung Lam Tu-wing Lam Wing-sui 8.91 85 97 Lau Wing-shum Lou Yan Lau Ying-lap 45 Leung Ho-in 97" -> This is messy. Three Lam entries: "Lam Tsung", "Lam Tu-wing", "Lam Wing-sui" with pages "8.91", "85", "97"? Then "Lau Wing-shum", "Lou Yan", "Lau Ying-lap 45", "Leung Ho-in 97". Too many.

"105 Leung Hon-chuen 85" -> "105" maybe page for previous.

"103 Leung Ka-chau 101"

"Lam Yam 81 Lau Yuk-kun 120 Leung Ka-ki 97"

"Lam Yan-san 57 Law. A. 67 Leung Kam-ming 123"

"Lam Young-chi 81 Law Chung-kwai 10. 12 Leung Kam-shing 85"

"Lam Yim 108 Law Fo-yung 31 Leung Kam-to 107"

"Lam Yu-hin 26 Law Yan-pak 91 Leung Kang-hin 8.26" -> "8.26" likely "8, 26".

"Lam Yuen-shi 99 Lawrence, F. E. 114 Leung Keung 17"

"Lamb, C. H. 120 Lawrence, W. M. 21 Lewy Ki 41" -> "Lewy Ki" likely "Lee Wai Ki" or "Leung Wai Ki"? But "Lewy Ki 41".

Also at top: "122 [viii] LIST OF OFFICERS." So page 122, [viii] is page number.

I need to produce a Markdown table. Since it's a list of officers with page numbers, I'll create a table with three columns: Name, Page, Name, Page, Name, Page. But the data is not perfectly aligned in threes. However, the original layout is three columns. I'll try to parse sequentially in rows of three entries.

Better approach: The OCR text is a linear list of name-page pairs. The original had three columns. I'll just create a single table with two columns: Name and Page, listing all entries in order. But the header says "OFFICE PAGE OFFICE PAGE OFFICE PAGE". That suggests three columns side by side. But for Markdown, a single two-column table might be simpler and more readable. However, the user said "reconstruct tabular data" using Markdown table syntax. I think a single table with two columns (Name, Page) is fine, but the original had three columns. I could make a table with six columns: Name1, Page1, Name2, Page2, Name3, Page3. But the data may not align perfectly in rows.

Given the messiness, I'll produce a two-column table: Officer, Page. That captures all data. But the header "OFFICE PAGE" repeated thrice indicates three columns. I'll note that it's a three-column layout but present as a single list.

Alternatively, I can create a table with three pairs of columns. But I need to decide row grouping. The OCR text seems to list entries in reading order: left column top to bottom, then middle column, then right column. But the OCR has read them in a mixed order? Actually the OCR output seems to be reading across rows: first row: Lai-Poon, C. 21 | Lambert, E. B. 120 | Lay, T. 15. Second row: Lai Pui-kon 13 | Lambert, W. O. 80 | Layne, D. 07. etc. So it's row-wise. So I can reconstruct rows of three entries each.

Let me try to parse row by row from the text. The text after "L-Continued." lines seems to be grouped in lines that correspond to rows. Each line in OCR seems to have three entries. For example:

Line 1: "Lai-Poon, C. 21 Lambert, E. B. 120 Lay, T. 15"

Line 2: "Lai Pui-kon 13 Lambert, W. 0. 80 Layne, D. 07"

Line 3: "Ini Shiu-tso 08 Laшprill, W. C. R.... 82 Lee, A. W. G8"

Line 4: "Lai Tze-inAN 121 Lane, L. P. 49 Lee Chuen 125"

Line 5: "Lai Yau 124, 126 Lang. E. P. H, 42 Lee Chung-wen 69"

Line 6: "Lai Yau-kit 28 Lang, J. C. 11 Lee, E. 59"

Line 7: "Lai Yau-yick 110 Langley, R. 96 Lee Ek-leong 6.3"

Line 8: "Lai Yew-ming 10 Lau, A. 62 Lee Fook 120"

Line 9: "Lai Ying 18 Lau Che-wa 19 Lec, J. 120"

Line 10: "Lai Yuen-ping 122 Lau Cheong B Lee, J. H. B. 1, 3, 4"

Line 11: "Lakeman, J. 62 Lau Cheuk-nam 18 . Lee Kam-ming 10"

Line 12: "Lain Chak-shing 48 Lau Cheung 108 Lee Kew 118"

Line 13: "Lam Cheuk-but 02 Lau Chuch 121 Lee King-shum 101"

Line 14: "Lam Chew 125 Lau Chuen-huen 16 Lee, M. E. 07"

Line 15: "Lan Chifung В Lau Chuen-ki 10 Lee Maü-lin 122"

Line 16: "Lam Chi-wie 71 Lau Chui 102 Lee Mun-fong 103"

Line 17: "Lam Chuen 19 Lau Chung-bin 85 Lee Nai-tong 120"

Line 18: "Lam Chun 125 Lau Chung-pun 90 Lee Po-tin 70"

Line 19: "Lam Chun-hi 21 Lau Fook-tseung 18 | Lee Pui-sum 21"

Line 20: "Lam Fai 21 Lau For-lam 6 Lee Shu-sun 44"

Line 21: "Lam Heung-wing 105 Lnu Fuk 100 Lee Suey-wing 86"

Line 22: "Lam Hon-cheong 105 Lau ilin. 106 Lee Tack-hing 69"

Line 23: "Lam Hung-ki 103 Lau flo-chuen 85 Lee Tsan-chiu 27"

Line 24: "Lam Iu-bun 6 Lau Hong 117 Lee Yau-yuD 12"

Line 25: "Lam. J. 93 Lau Ip-yuen 8+ Lee Yo-wing 10"

Line 26: "Lain Kai 19 Lau Kam-yung 16 Lee Yuk-him 75"

Line 27: "Lam Kai-tseung 39 Lau Kan 105 Lei Peng-ü 78"

Line 28: "Lam Karo 125 Lau King-ming 89 Lenaghan, J. 65"

Line 29: "Lam Kin-tong 120 Lau Ku 118 Leufestev, F. P. 28"

Line 30: "Lam King-shang 127 Lau Kun 87 Lenz, M. G. 17, 18"

Line 31: "Lani King-yuen 94 Lau Kwai, D. 123 Leo, K. 57"

Line 32: "Lou Kwan 40 Lan Kwoh-u 68. 71 Leong Yuen-lok 73"

Line 33: "Lam Leung 87 Lau Lai-san 78 Leung Biu-ling 116"

Line 34: "Lam Ling Lain, M. 16 Lau Lai-shang 68 Lau Lok 97 Leung Cheuk-ü 93" -> This line has 5 entries? Actually "Lam Ling" (no page), "Lain, M. 16", "Lau Lai-shang 68", "Lau Lok 97", "Leung Cheuk-ü 93". That's 5. Maybe "Lam Ling" belongs to previous row? But previous row ended with "Leung Biu-ling 116". So "Lam Ling" might be start of next row, but missing page. Then "Lain, M. 16" second column, "Lau Lai-shang 68" third column? But then "Lau Lok 97" and "Leung Cheuk-ü 93" extra. Could be that "Lam Ling" page is 106? Next line starts with "106 Leung Cheung 122". So maybe "Lam Ling 106" and then "Leung Cheung 122" is next row first column? But then "Lain, M. 16" etc. This is messy.

Line 35: "106 Leung Cheung 122"

Line 36: "Lam Ming 24 Lau Man 118 Leung Chik-wai 116"

Line 37: "Lam Pak 25 Lau Man-kui 98 Leung Ching-yu 45"

Line 38: "Lam Pak-to 101 L. On 148 Leung Chiu-tung 86"

Line 39: "Lam Ping-ki 105 Lau Pak-wah 39 Leung Choi 106"

Line 40: "Lam Poi 125 Lau Ping 106 Leung Chuk-hin 13"

Line 41: "Lam Pai 25 Jau Sam 118 Leung Chung-kan 60.84"

Line 42: "Lam Shai-tit 127 Lam Sher-song 21 Lau Shiu Lau Shiu-chung 108 Leung Chung-yin 105" -> 4 entries.

Line 43: "6 Leung, F. 56"

Line 44: "Lam Shiu-chi 73, 74 Lau Shuk-chong 8.91 Leung Fan 105"

Line 45: "Lam Shiu-fong Lam Shiu-huen 73 Lau Shuk-ying 99 Leung Fat 125"

Line 46: "21 Lau Sik-hung 20 Leung Fong 108"

Line 47: "Lan. Shiu-kwong 74 Lau Tak-cheuk 98 Leung Foo 17"

Line 48: "Lam Shiu-wa Lam Chu-tung 100 Lau Tin-chak 101 Leung Fung-ki 97"

Line 49: "28. 87 Lau Ting-tui 123 Leung Gon-ting 69"

Line 50: "Lam Shui-paug 26, 110 Lau Tsz-ping 8 Leung He-man 74"

Line 51: "Lan. Sik 21 Lau. V. L. BO Leung Hei 27"

Line 52: "Lam Sing-U 17 Lau Wing-hon 20 Leung Hi-cheong 116"

Line 53: "Lain Tin 14 Lau Wing-kwong 62 Leung Hin-cheong 117"

Line 54: "Lam Tsung Lam Tu-wing Lam Wing-sui 8.91 85 97 Lau Wing-shum Lou Yan Lau Ying-lap 45 Leung Ho-in 97" -> many.

Line 55: "105 Leung Hon-chuen 85"

Line 56: "103 Leung Ka-chau 101"

Line 57: "Lam Yam 81 Lau Yuk-kun 120 Leung Ka-ki 97"

Line 58: "Lam Yan-san 57 Law. A. 67 Leung Kam-ming 123"

Line 59: "Lam Young-chi 81 Law Chung-kwai 10. 12 Leung Kam-shing 85"

Line 60: "Lam Yim 108 Law Fo-yung 31 Leung Kam-to 107"

Line 61: "Lam Yu-hin 26 Law Yan-pak 91 Leung Kang-hin 8.26"

Line 62: "Lam Yuen-shi 99 Lawrence, F. E. 114 Leung Keung 17"

Line 63: "Lamb, C. H. 120 Lawrence, W. M. 21 Lewy Ki 41"

This is too messy to perfectly reconstruct rows. Given the instruction: "reconstruct tabular data using Markdown table syntax". I think the best is to create a single table with two columns: Officer and Page, listing all entries in the order they appear, correcting obvious OCR errors. That would be a faithful representation of the data.

But the original is a three-column index. However, the user didn't specify to preserve the three-column layout. They said "reconstruct tabular data". A two-column table is still tabular.

I'll produce a Markdown table with headers "Officer" and "Page". I'll clean up names and pages.

Let me compile a list of all name-page pairs from the above parsing, correcting obvious errors.

I'll go through each line and extract pairs.

I'll write a script mentally, but manually.

First, note that "OFFICE" likely means "Officer". I'll use "Officer".

Also, page numbers: some have commas, some have dots, some have "8.91" etc. I'll keep as they appear but correct obvious misreads: "G8" -> "68", "07" -> "7"? But "07" could be "7" or "07". "6.3" -> "63". "02" -> "102"? But "Lam Cheuk-but 02" maybe "102". "8+" -> "81". "В" -> "8". "8.91" -> "89, 91"? "8.26" -> "8, 26". "60.84" -> "60, 84". "BO" -> "80". "10. 12" -> "10, 12". "28. 87" -> "28, 87". "8.91" appears multiple times.

Also names: "Ini Shiu-tso" -> "Lai Shiu-tso". "Laшprill" -> "Lamprill". "Lai Tze-inAN" -> "Lai Tze-in An"? Maybe "Lai Tze-inan". I'll keep "Lai Tze-inan". "Lan. E. P. H," -> "Lang, E. P. H."? Actually "Lang. E. P. H," likely "Lang, E. P. H.".

"Lec, J." -> "Lee, J.".

"Lau Cheong B" -> "Lau Cheong 8".

"Lain Chak-shing" -> "Lam Chak-shing".

"Lam Cheuk-but 02" -> "Lam Cheuk-but 102".

"Lau Chuch" -> "Lau Chuk".

"Lan Chifung В" -> "Lam Chi-fung 8".

"Lnu Fuk" -> "Lau Fuk".

"Lau ilin." -> "Lau Lin".

"Lau flo-chuen" -> "Lau Fook-chuen".

"Lee Yau-yuD" -> "Lee Yau-yun".

"Lau Ip-yuen 8+" -> "Lau Ip-yuen 81".

"Lain Kai" -> "Lam Kai".

"Lani King-yuen" -> "Lam King-yuen".

"Lou Kwan" -> "Lau Kwan".

"Lan Kwoh-u" -> "Lam Kwoh-u".

"Lam Ling" (no page) -> maybe "Lam Ling 106" from next line "106". So pair "Lam Ling 106".

"Lain, M." -> "Lam, M.".

"Lam Shai-tit" -> "Lam Shai-tit".

"Lam Sher-song" -> "Lam Shek-song"? But keep "Lam Sher-song".

"Lau Shiu Lau Shiu-chung" -> duplicate, maybe "Lau Shiu-chung".

"Lan. Shiu-kwong" -> "Lam Shiu-kwong".

"Lam Shiu-wa Lam Chu-tung" -> two names: "Lam Shiu-wa" and "Lam Chu-tung". But only one page "100"? Actually "Lam Shiu-wa Lam Chu-tung 100" - maybe "Lam Shiu-wa" no page, "Lam Chu-tung 100". But then "Lau Tin-chak 101". So perhaps "Lam Shiu-wa" page missing, "Lam Chu-tung 100". I'll split.

"28. 87" -> maybe pages for "Lam Shiu-wa" and "Lam Chu-tung"? But "28. 87" appears next line. Could be "Lam Shiu-wa 28, 87". But then "Lau Ting-tui 123". I'll assume "Lam Shiu-wa 28, 87" and "Lam Chu-tung 100". But the line "Lam Shiu-wa Lam Chu-tung 100" suggests both on same line with page 100 for Chu-tung. Then next line "28. 87 Lau Ting-tui 123 Leung Gon-ting 69". So "28. 87" might be for "Lam Shiu-wa". I'll assign "Lam Shiu-wa 28, 87".

"Lam Tsung Lam Tu-wing Lam Wing-sui 8.91 85 97" -> three names with three pages: "Lam Tsung 8.91", "Lam Tu-wing 85", "Lam Wing-sui 97". But "8.91" likely "89, 91". I'll keep as "89, 91".

"Lau Wing-shum Lou Yan Lau Ying-lap 45" -> three names: "Lau Wing-shum", "Lou Yan", "Lau Ying-lap" with page 45? But "Leung Ho-in 97" follows. So maybe "Lau Wing-shum" no page, "Lou Yan" no page, "Lau Ying-lap 45". Then "Leung Ho-in 97". But "105 Leung Hon-chuen 85" next. This is messy.

Given the complexity, I'll produce a two-column table with all entries as they appear in the OCR text, but corrected for obvious errors, and keep the order. I'll not try to align in three columns.

I'll write the Markdown table.

First, the header: "# LIST OF OFFICERS" maybe with "[viii]" and "122" as page markers.

The OCR starts with "122 [viii] LIST OF OFFICERS." So I'll include that as a header.

Then the table.

Let me compile the list sequentially from the OCR text, line by line, extracting name-page pairs.

I'll go through the raw OCR text provided and parse.

The raw text:

"122

[viii]

LIST OF OFFICERS.

OFFICE

PAGE

OFFICE

PAGE

OFFICE

PAGE

J

J

J

L-Continued.

L-Continued.

L—Continued.

Lai-Poon, C.

21

Lambert, E. B.

120

Lay, T.

15

Lai Pui-kon

13

Lambert, W. 0.

80

Layne, D.

07

Ini Shiu-tso

08

Laшprill, W. C. R....

82

Lee, A. W.

G8

Lai Tze-inAN

121

Lane, L. P.

49

Lee Chuen

125

Lai Yau

124, 126

Lang. E. P. H,

42

Lee Chung-wen

69

Lai Yau-kit

28

Lang, J. C.

11

Lee, E.

59

Lai Yau-yick

110

Langley, R.

96

Lee Ek-leong

6.3

Lai Yew-ming

10

Lau, A.

62

Lee Fook

120

Lai Ying

18

Lau Che-wa

19

Lec, J.

120

Lai Yuen-ping

122

Lau Cheong

B

Lee, J. H. B.

1, 3, 4

Lakeman, J.

62

Lau Cheuk-nam

18

.

Lee Kam-ming

10

Lain Chak-shing

48

Lau Cheung

108

Lee Kew

118

Lam Cheuk-but

02 Lau Chuch

121

Lee King-shum

101

Lam Chew

125

Lau Chuen-huen

16

Lee, M. E.

07

Lan Chifung

В Lau Chuen-ki

10

Lee Maü-lin

122

Lam Chi-wie

71

Lau Chui

102

Lee Mun-fong

103

Lam Chuen

19 Lau Chung-bin

85

Lee Nai-tong

120

Lam Chun

125

Lau Chung-pun

90

Lee Po-tin

70

Lam Chun-hi

21 Lau Fook-tseung

18

| Lee Pui-sum

21

Lam Fai

21 Lau For-lam

6

Lee Shu-sun

44

Lam Heung-wing

105

Lnu Fuk

100

Lee Suey-wing

86

Lam Hon-cheong

105

Lau ilin.

106

Lee Tack-hing

69

Lam Hung-ki

103

Lau flo-chuen

85

Lee Tsan-chiu

27

Lam Iu-bun

6

Lau Hong

117

Lee Yau-yuD

12

Lam. J.

93 Lau Ip-yuen

8+

Lee Yo-wing

10

Lain Kai

19

Lau Kam-yung

16

Lee Yuk-him

75

Lam Kai-tseung

39 Lau Kan

105

Lei Peng-ü

78

Lam Karo

125

Lau King-ming

89

Lenaghan, J.

65

Lam Kin-tong

120

Lau Ku

118

Leufestev, F. P.

28

Lam King-shang

127

Lau Kun

87

Lenz, M. G.

17, 18

Lani King-yuen

94

Lau Kwai, D.

123

Leo, K.

57

Lou Kwan

40

Lan Kwoh-u

1. 71

Leong Yuen-lok

73

Lam Leung

87 Lau Lai-san

78

Leung Biu-ling

116

Lam Ling

Lain, M.

16 Lau Lai-shang 68 Lau Lok

97

Leung Cheuk-ü

93

106

Leung Cheung

122

Lam Ming

24

Lau Man

118

Leung Chik-wai

116

Lam Pak

25 Lau Man-kui

98

Leung Ching-yu

45

Lam Pak-to

101

L. On

148

Leung Chiu-tung

86

Lam Ping-ki

105

Lau Pak-wah

39

Leung Choi

106

Lam Poi

125

Lau Ping

106

Leung Chuk-hin

13

Lam Pai

25 Jau Sam

118

Leung Chung-kan

60.84

Lam Shai-tit

127

Lam Sher-song

21

Lau Shiu Lau Shiu-chung

108

Leung Chung-yin

105

6

Leung, F.

56

Lam Shiu-chi

73, 74

Lau Shuk-chong

8.91

Leung Fan

105

Lam Shiu-fong Lam Shiu-huen

73 Lau Shuk-ying

99

Leung Fat

125

21

Lau Sik-hung

20

Leung Fong

108

Lan. Shiu-kwong

74

Lau Tak-cheuk

98

Leung Foo

17

Lam Shiu-wa Lam Chu-tung

100

Lau Tin-chak

101

Leung Fung-ki

97

1. 87

Lau Ting-tui

123

Leung Gon-ting

69

Lam Shui-paug

26, 110

Lau Tsz-ping

8

Leung He-man

74

Lan. Sik

21

Lau. V. L.

BO

Leung Hei

27

Lam Sing-U

17

Lau Wing-hon

20

Leung Hi-cheong

116

Lain Tin

14

Lau Wing-kwong

62

Leung Hin-cheong

117

Lam Tsung

Lam Tu-wing

Lam Wing-sui

8.91

85

97 Lau Wing-shum

Lou Yan Lau Ying-lap

45

Leung Ho-in

97

105

Leung Hon-chuen

85

103

Leung Ka-chau

101

Lam Yam

81 Lau Yuk-kun

120

Leung Ka-ki

97

Lam Yan-san

57 Law. A.

67

Leung Kam-ming

123

Lam Young-chi

81

Law Chung-kwai

1. 12

Leung Kam-shing

85

Lam Yim

108

Law Fo-yung

31

Leung Kam-to

107

Lam Yu-hin

26

Law Yan-pak

91

Leung Kang-hin

8.26

Lam Yuen-shi

99

Lawrence, F. E.

114

Leung Keung

17

Lamb, C. H.

120

Lawrence, W. M.

21

Lewy Ki

41"

Now, I need to parse this into name-page pairs. The text is essentially a list where each name is followed by its page number, but sometimes the page number is on the next line. Also there are some artifacts like "J", "J", "J", "L-Continued." etc.

I'll write a simple parser: read tokens, but manually.

Better: I'll go through the text and pair each name with the following number, ignoring headers.

Let me list all lines with content:

1. 122
2. [viii]
3. LIST OF OFFICERS.
4. OFFICE
5. PAGE
6. OFFICE
7. PAGE
8. OFFICE
9. PAGE
10. J
11. J
12. J
13. L-Continued.
14. L-Continued.
15. L—Continued.
16. Lai-Poon, C.
17. 21
18. Lambert, E. B.
19. 120
20. Lay, T.
21. 15
22. Lai Pui-kon
23. 13
24. Lambert, W. 0.
25. 80
26. Layne, D.
27. 07
28. Ini Shiu-tso
29. 08
30. Laшprill, W. C. R....
31. 82
32. Lee, A. W.
33. G8
34. Lai Tze-inAN
35. 121
36. Lane, L. P.
37. 49
38. Lee Chuen
39. 125
40. Lai Yau
41. 124, 126
42. Lang. E. P. H,
43. 42
44. Lee Chung-wen
45. 69
46. Lai Yau-kit
47. 28
48. Lang, J. C.
49. 11
50. Lee, E.
51. 59
52. Lai Yau-yick
53. 110
54. Langley, R.
55. 96
56. Lee Ek-leong
57. 6.3
58. Lai Yew-ming
59. 10
60. Lau, A.
61. 62
62. Lee Fook
63. 120
64. Lai Ying
65. 18
66. Lau Che-wa
67. 19
68. Lec, J.
69. 120
70. Lai Yuen-ping
71. 122
72. Lau Cheong
73. B
74. Lee, J. H. B.
75. 1, 3, 4
76. Lakeman, J.
77. 62
78. Lau Cheuk-nam
79. 18
80. .
81. Lee Kam-ming
82. 10
83. Lain Chak-shing
84. 48
85. Lau Cheung
86. 108
87. Lee Kew
88. 118
89. Lam Cheuk-but
90. 02 Lau Chuch
91. 121
92. Lee King-shum
93. 101
94. Lam Chew
95. 125
96. Lau Chuen-huen
97. 16
98. Lee, M. E.
99. 07
100. Lan Chifung
101. В Lau Chuen-ki
102. 10
103. Lee Maü-lin
104. 122
105. Lam Chi-wie
106. 71
107. Lau Chui
108. 102
109. Lee Mun-fong
110. 103
111. Lam Chuen
112. 19 Lau Chung-bin
113. 85
114. Lee Nai-tong
115. 120
116. Lam Chun
117. 125
118. Lau Chung-pun
119. 90
120. Lee Po-tin
121. 70
122. Lam Chun-hi
123. 21 Lau Fook-tseung
124. 18
125. | Lee Pui-sum
126. 21
127. Lam Fai
128. 21 Lau For-lam
129. 6
130. Lee Shu-sun
131. 44
132. Lam Heung-wing
133. 105
134. Lnu Fuk
135. 100
136. Lee Suey-wing
137. 86
138. Lam Hon-cheong
139. 105
140. Lau ilin.
141. 106
142. Lee Tack-hing
143. 69
144. Lam Hung-ki
145. 103
146. Lau flo-chuen
147. 85
148. Lee Tsan-chiu
149. 27
150. Lam Iu-bun
151. 6
152. Lau Hong
153. 117
154. Lee Yau-yuD
155. 12
156. Lam. J.
157. 93 Lau Ip-yuen
158. 8+
159. Lee Yo-wing
160. 10
161. Lain Kai
162. 19
163. Lau Kam-yung
164. 16
165. Lee Yuk-him
166. 75
167. Lam Kai-tseung
168. 39 Lau Kan
169. 105
170. Lei Peng-ü
171. 78
172. Lam Karo
173. 125
174. Lau King-ming
175. 89
176. Lenaghan, J.
177. 65
178. Lam Kin-tong
179. 120
180. Lau Ku
181. 118
182. Leufestev, F. P.
183. 28
184. Lam King-shang
185. 127
186. Lau Kun
187. 87
188. Lenz, M. G.
189. 17, 18
190. Lani King-yuen
191. 94
192. Lau Kwai, D.
193. 123
194. Leo, K.
195. 57
196. Lou Kwan
197. 40
198. Lan Kwoh-u
199. 68. 71
200. Leong Yuen-lok
201. 73
202. Lam Leung
203. 87 Lau Lai-san
204. 78
205. Leung Biu-ling
206. 116
207. Lam Ling
208. Lain, M.
209. 16 Lau Lai-shang
210. 68 Lau Lok
211. 97
212. Leung Cheuk-ü
213. 93
214. 106
215. Leung Cheung
216. 122
217. Lam Ming
218. 24
219. Lau Man
220. 118
221. Leung Chik-wai
222. 116
223. Lam Pak
224. 25 Lau Man-kui
225. 98
226. Leung Ching-yu
227. 45
228. Lam Pak-to
229. 101
230. L. On
231. 148
232. Leung Chiu-tung
233. 86
234. Lam Ping-ki
235. 105
236. Lau Pak-wah
237. 39
238. Leung Choi
239. 106
240. Lam Poi
241. 125
242. Lau Ping
243. 106
244. Leung Chuk-hin
245. 13
246. Lam Pai
247. 25 Jau Sam
248. 118
249. Leung Chung-kan
250. 60.84
251. Lam Shai-tit
252. 127
253. Lam Sher-song
254. 21
255. Lau Shiu Lau Shiu-chung
256. 108
257. Leung Chung-yin
258. 105
259. 6
260. Leung, F.
261. 56
262. Lam Shiu-chi
263. 73, 74
264. Lau Shuk-chong
265. 8.91
266. Leung Fan
267. 105
268. Lam Shiu-fong Lam Shiu-huen
269. 73 Lau Shuk-ying
270. 99
271. Leung Fat
272. 125
273. 21
274. Lau Sik-hung
275. 20
276. Leung Fong
277. 108
278. Lan. Shiu-kwong
279. 74
280. Lau Tak-cheuk
281. 98
282. Leung Foo
283. 17
284. Lam Shiu-wa Lam Chu-tung
285. 100
286. Lau Tin-chak
287. 101
288. Leung Fung-ki
289. 97
290. 28. 87
291. Lau Ting-tui
292. 123
293. Leung Gon-ting
294. 69
295. Lam Shui-paug
296. 26, 110
297. Lau Tsz-ping
298. 8
299. Leung He-man
300. 74
301. Lan. Sik
302. 21
303. Lau. V. L.
304. BO
305. Leung Hei
306. 27
307. Lam Sing-U
308. 17
309. Lau Wing-hon
310. 20
311. Leung Hi-cheong
312. 116
313. Lain Tin
314. 14
315. Lau Wing-kwong
316. 62
317. Leung Hin-cheong
318. 117
319. Lam Tsung
320. Lam Tu-wing
321. Lam Wing-sui
322. 8.91
323. 85
324. 97 Lau Wing-shum
325. Lou Yan Lau Ying-lap
326. 45
327. Leung Ho-in
328. 97
329. 105
330. Leung Hon-chuen
331. 85
332. 103
333. Leung Ka-chau
334. 101
335. Lam Yam
336. 81 Lau Yuk-kun
337. 120
338. Leung Ka-ki
339. 97
340. Lam Yan-san
341. 57 Law. A.
342. 67
343. Leung Kam-ming
344. 123
345. Lam Young-chi
346. 81
347. Law Chung-kwai
348. 10. 12
349. Leung Kam-shing
350. 85
351. Lam Yim
352. 108
353. Law Fo-yung
354. 31
355. Leung Kam-to
356. 107
357. Lam Yu-hin
358. 26
359. Law Yan-pak
360. 91
361. Leung Kang-hin
362. 8.26
363. Lam Yuen-shi
364. 99
365. Lawrence, F. E.
366. 114
367. Leung Keung
368. 17
369. Lamb, C. H.
370. 120
371. Lawrence, W. M.
372. 21
373. Lewy Ki
374. 41

Now, I need to pair names with pages. The pattern: name appears, then page appears. But sometimes multiple names before a page? Actually from the list, it seems each name is followed by its page, but sometimes the page is on the same line in OCR but split in this line-by-line representation. In the above line list, each line is a separate OCR line. But the original OCR text had lines with multiple entries. However, in this line list, I've split by newline. But the raw text had newlines. Looking at the raw text, it seems each name and page are on separate lines? For example:

"Lai-Poon, C.

21

Lambert, E. B.

120

Lay, T.

15"

So indeed, each name on one line, page on next. But later we see "Lam Cheuk-but

02 Lau Chuch

121" - here "Lam Cheuk-but" on line, then "02 Lau Chuch" on next? Actually raw: "Lam Cheuk-but

02 Lau Chuch

121". So "02 Lau Chuch" is one line? That's messy.

But from the line list I made, I split by newline in the raw text. The raw text has newlines. Let's look at the raw text provided: it's a block of text with line breaks. I copied it as a block. In the user message, it's formatted with line breaks. So each line in the user message is a line. But the user message shows lines like:

"Lam Cheuk-but

02 Lau Chuch

121"

So three lines. So my line list is accurate.

Thus, the sequence is: name, page, name, page, ... but sometimes a line contains both a page and a name (like "02 Lau Chuch"). That indicates OCR merged two columns.

Given the complexity, I think the best is to produce a two-column table by reading the raw text sequentially and pairing each name with the next numeric page, but we have to handle merged lines.

Given the time, I'll produce a Markdown table with two columns: Officer and Page, by manually extracting pairs from the line list, using logic: if a line looks like a name (contains letters, commas, etc.) and the next line looks like a page (numbers, commas, dots), then pair them. If a line contains both, split.

But doing that manually for 374 lines is tedious. However, I can write a script in my mind? But as an AI, I can process the list programmatically in my reasoning. I'll simulate.

I'll go through the line list and build pairs.

Initialize empty list.

Iterate lines with index.

If line matches a name pattern (contains letters, not just numbers and punctuation), and next line matches page pattern (digits, commas, dots, maybe letters like 'B', 'G8'), then pair.

But some lines are headers or artifacts.

Let's define page pattern: string that consists of digits, commas, periods, spaces, maybe 'B', 'G8', 'BO', 'В', '|', etc. But names also have numbers sometimes (e.g., "Lai Tze-inAN 121" but that's on same line? In line list, "Lai Tze-inAN" line 34, "121" line 35. So separate.

But there are lines like "02 Lau Chuch" which is page "02" and name "Lau Chuch". So we need to split.

Given the difficulty, perhaps the user expects me to output the corrected text as a Markdown table replicating the three-column layout? But the instruction: "reconstruct tabular data using Markdown table syntax." The original is a three-column table. I could create a Markdown table with six columns: Officer1, Page1, Officer2, Page2, Officer3, Page3. But the data rows may not align perfectly.

Given the time, I'll produce a two-column table with all entries, as that is a faithful reconstruction of the data. I'll include a note? But the instruction says no commentary. So just the table.

I'll write the table in Markdown.

First, I'll create a list of (officer, page) by parsing the raw text with a simple algorithm: split the raw text by whitespace? But names have spaces.

Alternative: The raw text is essentially a list of alternating name and page. I'll join all lines into a single string, then split by newline, then process.

But I can do it manually by scanning the line list I made.

Let me write a quick mental script:

pairs = []

i = 0

while i < len(lines):

line = lines[i].strip()

if not line: i+=1; continue

skip header lines

if line in ['122', '[viii]', 'LIST OF OFFICERS.', 'OFFICE', 'PAGE', 'J', 'L-Continued.', 'L—Continued.']:

i+=1

continue

if line looks like a page (starts with digit or contains only digits, commas, dots, letters like B, G, etc.)

but names can start with digits? Unlikely.

Heuristic: if line matches ^[\d\.,\sBVG]+$ maybe page.

But better: if the line contains a comma or period and letters, it's a name.

Actually, names have letters, pages are mostly numbers.

So if line has any letter (A-Za-z), it's a name. But pages like "G8", "BO", "В" have letters.

However, "G8" is page for "Lee, A. W.".

So we need context: a name is followed by a page.

Since the list is alternating, we can assume the first non-header line is a name, then page, then name, etc.

But there are merged lines.

Given the merged lines, the alternating pattern breaks.

Given the difficulty, I'll output the raw text cleaned up as a Markdown table with two columns by manually transcribing the pairs as they appear in the original three-column layout? But I don't have the original layout.

Maybe the user expects me to output the text as a corrected list, not necessarily a table. But they said "reconstruct tabular data using Markdown table syntax."

Looking at the OCR, it's clearly a table with three columns. The header "OFFICE PAGE OFFICE PAGE OFFICE PAGE" indicates three columns. The data follows in three columns. The OCR has read it row by row? Actually, the OCR output seems to be reading the three columns sequentially? But the text shows "Lai-Poon, C. 21 Lambert, E. B. 120 Lay, T. 15" which is first row, three entries. Then next row: "Lai Pui-kon 13 Lambert, W. 0. 80 Layne, D. 07". So it's row-wise. So the OCR has preserved rows. Good! So each "row" in the OCR text corresponds to a row in the table. In the raw text, each row appears as a block of lines? But in the user message, the text is formatted with line breaks that seem to correspond to the OCR lines. However, the user message shows the text with line breaks that might be the original OCR line breaks. For example, the first few lines:

"122

[viii]

LIST OF OFFICERS.

OFFICE

PAGE

OFFICE

PAGE

OFFICE

PAGE

J

J

J

L-Continued.

L-Continued.

L—Continued.

Lai-Poon, C.

21

Lambert, E. B.

120

Lay, T.

15

Lai Pui-kon

13

Lambert, W. 0.

80

Layne, D.

07"

This suggests that the OCR output each cell on a new line. So the table cells are each on separate lines. The three columns are interleaved: first column cells, then second column cells, then third column cells? But here we see: Lai-Poon, C. (col1), 21 (col1 page), Lambert, E. B. (col2), 120 (col2 page), Lay, T. (col3), 15 (col3 page). Then next row: Lai Pui-kon (col1), 13 (col1 page), Lambert, W. 0. (col2), 80 (col2 page), Layne, D. (col3), 07 (col3 page). So the OCR read the table row by row, and for each row, it output the six cells in order (name1, page1, name2, page2, name3, page3), each on a new line. That is perfect! So the raw text is a linear sequence of cells: for each row, six lines: Officer1, Page1, Officer2, Page2, Officer3, Page3.

But later, the line breaks may not be perfectly consistent because of merged cells. But the pattern holds for the beginning.

Thus, we can parse the entire list as a sequence of cells, grouping every 6 lines into a row (after skipping headers). However, there are header lines and "J" lines and "L-Continued." lines. Also, some rows may have missing cells? But we can attempt.

Let's list all lines after the header, ignoring empty lines.

From the user message, the text lines (non-empty) are:

1. 122
2. [viii]
3. LIST OF OFFICERS.
4. OFFICE
5. PAGE
6. OFFICE
7. PAGE
8. OFFICE
9. PAGE
10. J
11. J
12. J
13. L-Continued.
14. L-Continued.
15. L—Continued.
16. Lai-Poon, C.
17. 21
18. Lambert, E. B.
19. 120
20. Lay, T.
21. 15
22. Lai Pui-kon
23. 13
24. Lambert, W. 0.
25. 80
26. Layne, D.
27. 07
28. Ini Shiu-tso
29. 08
30. Laшprill, W. C. R....
31. 82
32. Lee, A. W.
33. G8
34. Lai Tze-inAN
35. 121
36. Lane, L. P.
37. 49
38. Lee Chuen
39. 125
40. Lai Yau
41. 124, 126
42. Lang. E. P. H,
43. 42
44. Lee Chung-wen
45. 69
46. Lai Yau-kit
47. 28
48. Lang, J. C.
49. 11
50. Lee, E.
51. 59
52. Lai Yau-yick
53. 110
54. Langley, R.
55. 96
56. Lee Ek-leong
57. 6.3
58. Lai Yew-ming
59. 10
60. Lau, A.
61. 62
62. Lee Fook
63. 120
64. Lai Ying
65. 18
66. Lau Che-wa
67. 19
68. Lec, J.
69. 120
70. Lai Yuen-ping
71. 122
72. Lau Cheong
73. B
74. Lee, J. H. B.
75. 1, 3, 4
76. Lakeman, J.
77. 62
78. Lau Cheuk-nam
79. 18
80. .
81. Lee Kam-ming
82. 10
83. Lain Chak-shing
84. 48
85. Lau Cheung
86. 108
87. Lee Kew
88. 118
89. Lam Cheuk-but
90. 02 Lau Chuch
91. 121
92. Lee King-shum
93. 101
94. Lam Chew
95. 125
96. Lau Chuen-huen
97. 16
98. Lee, M. E.
99. 07
100. Lan Chifung
101. В Lau Chuen-ki
102. 10
103. Lee Maü-lin
104. 122
105. Lam Chi-wie
106. 71
107. Lau Chui
108. 102
109. Lee Mun-fong
110. 103
111. Lam Chuen
112. 19 Lau Chung-bin
113. 85
114. Lee Nai-tong
115. 120
116. Lam Chun
117. 125
118. Lau Chung-pun
119. 90
120. Lee Po-tin
121. 70
122. Lam Chun-hi
123. 21 Lau Fook-tseung
124. 18
125. | Lee Pui-sum
126. 21
127. Lam Fai
128. 21 Lau For-lam
129. 6
130. Lee Shu-sun
131. 44
132. Lam Heung-wing
133. 105
134. Lnu Fuk
135. 100
136. Lee Suey-wing
137. 86
138. Lam Hon-cheong
139. 105
140. Lau ilin.
141. 106
142. Lee Tack-hing
143. 69
144. Lam Hung-ki
145. 103
146. Lau flo-chuen
147. 85
148. Lee Tsan-chiu
149. 27
150. Lam Iu-bun
151. 6
152. Lau Hong
153. 117
154. Lee Yau-yuD
155. 12
156. Lam. J.
157. 93 Lau Ip-yuen
158. 8+
159. Lee Yo-wing
160. 10
161. Lain Kai
162. 19
163. Lau Kam-yung
164. 16
165. Lee Yuk-him
166. 75
167. Lam Kai-tseung
168. 39 Lau Kan
169. 105
170. Lei Peng-ü
171. 78
172. Lam Karo
173. 125
174. Lau King-ming
175. 89
176. Lenaghan, J.
177. 65
178. Lam Kin-tong
179. 120
180. Lau Ku
181. 118
182. Leufestev, F. P.
183. 28
184. Lam King-shang
185. 127
186. Lau Kun
187. 87
188. Lenz, M. G.
189. 17, 18
190. Lani King-yuen
191. 94
192. Lau Kwai, D.
193. 123
194. Leo, K.
195. 57
196. Lou Kwan
197. 40
198. Lan Kwoh-u
199. 68. 71
200. Leong Yuen-lok
201. 73
202. Lam Leung
203. 87 Lau Lai-san
204. 78
205. Leung Biu-ling
206. 116
207. Lam Ling
208. Lain, M.
209. 16 Lau Lai-shang
210. 68 Lau Lok
211. 97
212. Leung Cheuk-ü
213. 93
214. 106
215. Leung Cheung
216. 122
217. Lam Ming
218. 24
219. Lau Man
220. 118
221. Leung Chik-wai
222. 116
223. Lam Pak
224. 25 Lau Man-kui
225. 98
226. Leung Ching-yu
227. 45
228. Lam Pak-to
229. 101
230. L. On
231. 148
232. Leung Chiu-tung
233. 86
234. Lam Ping-ki
235. 105
236. Lau Pak-wah
237. 39
238. Leung Choi
239. 106
240. Lam Poi
241. 125
242. Lau Ping
243. 106
244. Leung Chuk-hin
245. 13
246. Lam Pai
247. 25 Jau Sam
248. 118
249. Leung Chung-kan
250. 60.84
251. Lam Shai-tit
252. 127
253. Lam Sher-song
254. 21
255. Lau Shiu Lau Shiu-chung
256. 108
257. Leung Chung-yin
258. 105
259. 6
260. Leung, F.
261. 56
262. Lam Shiu-chi
263. 73, 74
264. Lau Shuk-chong
265. 8.91
266. Leung Fan
267. 105
268. Lam Shiu-fong Lam Shiu-huen
269. 73 Lau Shuk-ying
270. 99
271. Leung Fat
272. 125
273. 21
274. Lau Sik-hung
275. 20
276. Leung Fong
277. 108
278. Lan. Shiu-kwong
279. 74
280. Lau Tak-cheuk
281. 98
282. Leung Foo
283. 17
284. Lam Shiu-wa Lam Chu-tung
285. 100
286. Lau Tin-chak
287. 101
288. Leung Fung-ki
289. 97
290. 28. 87
291. Lau Ting-tui
292. 123
293. Leung Gon-ting
294. 69
295. Lam Shui-paug
296. 26, 110
297. Lau Tsz-ping
298. 8
299. Leung He-man
300. 74
301. Lan. Sik
302. 21
303. Lau. V. L.
304. BO
305. Leung Hei
306. 27
307. Lam Sing-U
308. 17
309. Lau Wing-hon
310. 20
311. Leung Hi-cheong
312. 116
313. Lain Tin
314. 14
315. Lau Wing-kwong
316. 62
317. Leung Hin-cheong
318. 117
319. Lam Tsung
320. Lam Tu-wing
321. Lam Wing-sui
322. 8.91
323. 85
324. 97 Lau Wing-shum
325. Lou Yan Lau Ying-lap
326. 45
327. Leung Ho-in
328. 97
329. 105
330. Leung Hon-chuen
331. 85
332. 103
333. Leung Ka-chau
334. 101
335. Lam Yam
336. 81 Lau Yuk-kun
337. 120
338. Leung Ka-ki
339. 97
340. Lam Yan-san
341. 57 Law. A.
342. 67
343. Leung Kam-ming
344. 123
345. Lam Young-chi
346. 81
347. Law Chung-kwai
348. 10. 12
349. Leung Kam-shing
350. 85
351. Lam Yim
352. 108
353. Law Fo-yung
354. 31
355. Leung Kam-to
356. 107
357. Lam Yu-hin
358. 26
359. Law Yan-pak
360. 91
361. Leung Kang-hin
362. 8.26
363. Lam Yuen-shi
364. 99
365. Lawrence, F. E.
366. 114
367. Leung Keung
368. 17
369. Lamb, C. H.
370. 120
371. Lawrence, W. M.
372. 21
373. Lewy Ki
374. 41

Now, after the header (lines 1-14), the data starts at line 15. The pattern: each row has 6 cells: Officer1, Page1, Officer2, Page2, Officer3, Page3. But some lines contain two cells (e.g., line 89: "02 Lau Chuch" - that's Page1 and Officer2 merged). Line 100: "В Lau Chuen-ki" - Page1? Actually line 99: "Lan Chifung", line 100: "В Lau Chuen-ki", line 101: "10". So line 100 has two cells. Similarly, line 111: "19 Lau Chung-bin" - Page1 and Officer2. Line 122: "21 Lau Fook-tseung". Line 124: "| Lee Pui-sum" - maybe Officer3? Line 127: "21 Lau For-lam". Line 139: "Lau ilin." - that's Officer2? Line 156: "93 Lau Ip-yuen". Line 167: "39 Lau Kan". Line 198: "68. 71" - that's Page2? Actually line 197: "Lan Kwoh-u", line 198: "68. 71", line 199: "Leong Yuen-lok". So line 198 is Page2. Line 202: "87 Lau Lai-san". Line 207: "Lam Ling" (Officer1), line 208: "Lain, M." (Officer2?), line 209: "16 Lau Lai-shang" (Page2 and Officer3?), line 210: "68 Lau Lok" (Page3 and Officer1 next row?), line 211: "Leung Cheuk-ü" (Officer2?), line 212: "93" (Page2?), line 213: "106" (Page3?), line 214: "Leung Cheung" (Officer1 next row?), line 215: "122" (Page1). This gets messy.

But the initial rows are clean. The merged lines indicate that the OCR sometimes combined two cells in one line. To reconstruct the table, we need to split those merged lines.

Given the complexity, perhaps the best is to output the data as a single list of officers and pages, as a two-column table, because the three-column layout is just a formatting choice. The user said "reconstruct tabular data". A two-column table is tabular.

I'll produce a Markdown table with two columns: Officer and Page. I'll extract all officer-page pairs from the sequence, correcting obvious OCR errors.

I'll write a programmatic approach in my reasoning: iterate through the lines after header, and whenever we see a line that looks like an officer name (contains letters, not just numbers), and the next line looks like a page (numbers, commas, dots), pair them. But merged lines break this.

Given the time constraints, I'll manually create the table by transcribing the pairs as they appear in the original three-column layout, but I'll do it for the first few rows to show the pattern, but the user expects the whole thing.

But the user provided the entire OCR text. They want the proofread text. I should output the entire corrected list.

I think I can produce a two-column table by reading the raw text as a sequence of tokens. Since I'm an AI, I can process the list I have.

Let me write a quick algorithm in my mind to parse the line list into pairs, handling merged lines by splitting on patterns.

But maybe I can cheat: The user might not expect perfect reconstruction; they want the text proofread. Since the OCR is of an index, the proofread text should be a clean index. I'll output a Markdown table with two columns, listing all names and pages in the order they appear, with corrections.

I'll start from line 15 and go through the line list, using a state machine.

I'll simulate:

Initialize list pairs = [].

i = 15 (0-indexed? but I'll use 1-indexed from above).

While i <= 373:

line = lines[i].strip()

if line is empty: i++; continue

Check if line is a page-like: matches ^[\d\.,\sBVG|]+$ maybe.

But names can have numbers (e.g., "Lai Tze-inAN" has no numbers, "Lam Cheuk-but" no numbers). So if line contains letters and not just numbers, it's a name.

However, merged lines have both.

Strategy: If line contains a space and the part after space looks like a page, split.

But let's do a simpler approach: Since the original is three columns, but we want a flat list, we can just take all lines that are not headers, and pair them sequentially: first non-header is name, second is page, third is name, fourth is page, etc. But merged lines break the count.

Given the difficulty, I'll output the data as a single Markdown table with two columns by manually writing the pairs from the initial clean rows and then for the rest, I'll do my best.

But the user will see the output. I need to provide a complete answer.

Given the time, I'll produce a two-column table with all entries from the line list, assuming each odd line (after header) is a name and each even line is a page, but skipping merged lines by splitting them.

I'll write a script in my reasoning to parse the line list.

Let me write a Python-like parser in my head.

lines = [list from 1 to 373]

Start from line 15 (index 14 in zero-based). But there are header lines up to line 14. So data starts at line 15.

I'll create a list of tokens by splitting merged lines.

Define a function to split a line into tokens: if line matches pattern of page followed by name (e.g., "02 Lau Chuch"), split into ["02", "Lau Chuch"]. Similarly "В Lau Chuen-ki" -> ["В", "Lau Chuen-ki"]. "19 Lau Chung-bin" -> ["19", "Lau Chung-bin"]. "21 Lau