Are you able to always solve the test cipher? Indeed it delivers a great result.

Have the homophones in your test cipher been used in sequences?

Yes, always solves with AZdecrypt. 25% sequential homophone randomization.

Here’s another with no sequential homophones. It does not matter.

71  56  90  3   72  3   40  35  35  71  50  6   7   32  65  89  56
100 69  55  57  53  12  64  100 83  73  86  13  59  74  27  36  57
33  31  36  5   90  14  1   64  81  8   29  39  17  12  92  73  67
43  98  79  90  2   35  97  98  48  37  90  84  52  48  53  27  60
71  50  82  16  60  63  99  29  29  25  34  87  69  60  57  11  58
13  100 27  75  5   86  13  91  67  95  81  70  59  82  20  62  50
48  32  29  8   36  80  94  92  71  81  94  56  24  31  53  2   84
87  65  41  26  84  84  34  99  15  32  73  33  40  98  28  6   26
61  95  34  15  4   54  67  39  81  70  64  78  82  16  51  90  46
56  97  92  48  4   22  7   4   51  4   45  10  55  26  73  40  59
72  21  25  68  69  100 91  14  55  29  91  42  62  5   28  95  87
14  86  5   6   23  8   88  29  18  65  10  30  64  99  66  17  19
90  54  33  75  28  85  47  44  54  42  60  9   39  80  54  89  94
47  73  74  66  26  14  93  34  82  67  75  87  49  42  95  5   90
52  83  95  93  37  97  46  35  9   55  47  39  9   24  47  45  71
92  7   75  47  53  77  83  57  55  75  68  76  94  44  44  78  42
4   97  42  43  21  25  30  71  35  46  72  77  19  97  46  44  69
4   10  8   81  39  81  23  64  84  11  21  72  64  93  37  71  2
46  50  99  82  48  86  96  55  38  65  58  15  23  5   75  15  39
69  100 10  11  88  34  100 38  24  12  37  40  35  44  78  18  38

Jarlve, you are probably right with what you say (otherwise I wouldn’t get an at least partial solution of your cipher, either ).

I continued to try on the cipher ‘as it is’, because I still believe in a fair chance that it is solvable as a homophone substitution without transposition. Some progress, at least..I was able to expand the Python code similar to the following pseudo-code:

SET VARIABLES
dictionary = (word1, word2,...word7000) [i][now words of length 5-10 letters][/i]
bigrams = (EN, ER,....LS) [i][frequent ones, as they are repeating at least once][/i]
iofbc = (ENTER, THERE,...) [i][overlapping repeating trigrams][/i]
- all above ~185,000 different sets of variables ('line') -

SEARCH FUNCTION
search for words in dictionary >0 [i][Aho-Corasick-Algorithm][/i]

CREATE FCCP-LINES
read line1 of 185,000, then go next
cipher phrase: chain #1 = e.g. M+pl+P+pl+Z+Q+H+F+B+c+Y
---if words in chain #1 found >0: add variables
---chain #2 = e.g. M+q+G+H+Q+c+t+pl+L
------if words in chain #2 found >0: add variables
------chain #3....
...
------------------if words in chain #9 found >0
------------------print chain#1, chain#2, chain#3...chain#9, word found in chain #1, word found in chain #2.....word found in chain #9.

The idea is, based on the variables set, to find any word in a specific string location of the cipher. The program then expands usually two to three variables with each step to create a second, third, fourth etc. string from the cipher. Only if the program finds any word in the previous string, the program continues to the next string. The program also covers all words found in a string.

What is quite nice is that each time I add another string, the more homophones are ‘covered’.

Results, so far, was that the program was able to find eight (!) different words in the cipher (as I had shown previously finding approximately 5 words). Now I do a run with the program to find a minimum of nine words in various spots of the cipher.

Not many configurations would allow nine different words in the 340 cipher (one may want to try to enter nine words in Oranchak’s webtoy..).

Below you find some illustration in which areas the program is looking for words. Meanwhile, the whole setting covers approximately 60% of the cipher (as the homophones not only appear in the strings underlined but also elsewhere).

QT

Excel is powerful..over the last days I created a small (=partial) CLEARTEXT GENERATOR for the 340 cipher. This is how it works:

First, we know about the following two sequences in the Z340:

We now use a dictionary (this time a large one). We then assume that in sequence no. 2 there is at least one word of length >4 letters. Although this could also not be the case, this possibility is still a realistic assumption (as long as Z had not only used short or extremely long words in that specific sequence).

However, we still have no idea, where such a word of length >4 would actually start.

Now the pattern matching method helps us out. The word ‘boob’, for example, can be placed into a cipher structure like ‘CDDC’ or, for homophone ciphers even ‘CDJC’ or ‘CDJK’, but not into a cipher structure like ‘CDCJ’ (try it, if you want). ‘C’ is ‘C’ and the letter ‘b’ is definitely not an ‘o’.

Thus, not all words from the dictionary can be placed onto all positions of the sequence. This because some of the homophones ocurring in the sequence are repeating (eg. the double ‘++’).

With the support of Cryptool, it was possible to place every single word (of different length, but at least >4) onto any position in sequence 2. All of the previous under consideration of the cipher pattern as well as the possibility of homophones being used (polyalphabet, e.g. ‘CDJK’). Starting from homophone #1 of the sequence, checking the whole dictionary for the pattern, then homophone #2 etc.

This results in a list of approx. 150,000 words on specific positions in sequence no. 2.

After this pattern-matching (cracking) process has been done – which was, by the way, described in an early NSA paper by Friedman, ‘Military Cryptanalysis’, 1952 – there are still additional steps to be done:

After defining a letter for the ‘+’ symbol, e.g. the letter ‘L’ or ‘S’, we can still add a list of 5-grams for sequence no. 1.

This because sequence no. 1, most likely, contains two frequent, overlapping trigrams. ‘Frequent’, because these overlapping trigrams actually occur twice in the cipher although homophones are used (shuffling the alphabet all the time..). Non-frequent trigrams rather would not occur twice or at least not in combination with a second also repeating trigram. This can be argued but one may expect two repating trigrams showing up in any homophone cipher anyway, as some frequent trigrams (e.g. ‘AND’ or ‘THE’) would indeed statistically occur around 6-8 times in a 340 letter text.

Now if we combine all of the above , we end up with a 20MB Excel file and millions of rather complicated formulas (e.g. ‘first letter equal to ‘+’ and second letter equal to the third letter of the 5-gram but length of the word =8‘ etc.). To cover all those combinations, millions of calculations are performed ‘in the background’ to find all combinations of ‘+’ symbol, 5-gram, sequence pattern and of course words.

Astonishing were the results:

For example, if you select the letter ‘S’ in combination with the 5-gram ‘THECO’, there are only 79 values found (from the whole dictionary) that actually match the pattern structure of sequence no.2 (at any spot).

Based on a dictionary of 50,000 words, this represents a ratio of 79:50,000, which is equal to an exclusion of 99.84% of all words of the dictionary (with that specific setting). All of this is done based on NSA Friedman’s millitary cryptanalisys method.

Following the previous example, it was possible to find out that if you use ‘S’ and ‘THECO’, you will be able to partially complete the sequence no. 2 with e.g. the word ‘SEDUCTRESS’ but 78 other words such as ‘DOCTOR’ or ‘PASSPORT’. You can try this in Oranchak’s webtoy, too. It is not possible, however, to enter the word ‘CROSSROAD’. But to enter this word is possible, if you chose the 5-gram ‘CTION’ instead of ‘THECO’).

That only a very small amount of words is found under such pre-setting is quite satisfying. It opens at least a chance to crack that cipher.

Conclusion:
Considering the most likely 5-grams (e.g. 30) in sequence no. 1 results in approximately 2,400 potential cleartext phrases (per each letter chosen for ‘+’). This, of course, including at least one full word of length >4. It is possible, that one of the examples already found (like discussed above) was indeed once written by Zodiac.

In other words:
Enter one letter for the ‘+’ symbol, add a frequent 5-gram for sequence no. 1 and with a good chance you get some potential cleartext (list of only 50-100 words). Based on such a large dictionary (+50,000), other cleartext is unlikely (assuming a standard homophone substitution).

Or described as sort of a promise:
If you give me the correct letter for the ‘+’ symbol as well as the correct 5-gram for sequence no. 1, you will receive 23-26% cleartext of the 340 cipher in return (will be explained later). This, including a list of approximately 50-100 alternatives, which may match the pattern of sequence no. 2, too.

For Excel, imo, this is quite surprising. We may estimate:

Approximately a max. of 10 letters for the ‘+’ symbol (I believe ins ‘S’ or ‘L’ but ok – at least it’d be a frequent one). An estimated 200 different 5-grams consisting of repeating, thus frequent trigrams (overlapping each other). Approximately 70-100 results per configuration. All this leads us to approx.

10 x 200 x 70 = 140,000

potential settings. Those may further be used for additional computation (e.g. cross-checking with another sequence of the cipher, continuing with pattern matching, trial & error etc.). As an optimist, however, I’d say only 2 letters for the ‘+’ symbol are in question and a maximum of 60 different 5-grams may be needed; leading us to:

2 x 60 x 70 = 8,400

potential settings, with one of it leading to Z’s cleartext. Optimism, however, is just a lack of information..

With the correct setting, all depending on the position and length of the word, approximately 80 to 90 homophones of the Z340 are then ‘solved’.This is equal to a total of 23%-26% of the cipher!

As long as someone doesn’t have an IQ of +170 or being the world champion in scrabble, additional computation is most likely needed to then convert the complete cipher into cleartext. Needless to say that, if you have choosen the wrong settings from the beginning (e.g. wrong 5-gram), Z would continue to be ‘crackproof’ until you have found the right setting.

For those interested, here is how many of the formulas used acutally look like (German languag, this specific one actually found the word ‘seductress’..no need to understand the formula as it is here shown out of context)

=WENN(UND(LÄNGE($Y19510)>11;$A19510=$I19510;$A19510=$AB$1;$B19510=RECHTS(LINKS(AY$1;3);1);$E19510=RECHTS(LINKS(AY$1;4);1);$F19510=LINKS(AY$1;1);$D19510=$L19510;$G19510=$K19510;$I19510=$J19510);$Y19510;WENN(UND(LÄNGE($Y19510)=11;$A19510=$I19510;$A19510=$AB$1;$B19510=RECHTS(LINKS(AY$1;3);1);$E19510=RECHTS(LINKS(AY$1;4);1);$F19510=LINKS(AY$1;1);$G19510=$K19510;$I19510=$J19510);$Y19510;WENN(UND(LÄNGE($Y19510)=10;$A19510=$I19510;$A19510=$AB$1;$B19510=RECHTS(LINKS(AY$1;3);1);$E19510=RECHTS(LINKS(AY$1;4);1);$F19510=LINKS(AY$1;1);$I19510=$J19510);$Y19510;WENN(UND(LÄNGE($Y19510)=9;$A19510=$I19510;$A19510=$AB$1;$B19510=RECHTS(LINKS(AY$1;3);1);$E19510=RECHTS(LINKS(AY$1;4);1);$F19510=LINKS(AY$1;1));$Y19510;WENN(UND(LÄNGE($Y19510)>5;LÄNGE($Y19510)<9;$A19510=$AB$1;$B19510=RECHTS(LINKS(AY$1;3);1);$E19510=RECHTS(LINKS(AY$1;4);1);$F19510=LINKS(AY$1;1));$Y19510;WENN(UND(LÄNGE($Y19510)=5;$A19510=$AB$1;$B19510=RECHTS(LINKS(AY$1;3);1);$E19510=RECHTS(LINKS(AY$1;4);1));$Y19510;""))))))

QT

Is this the Friedman book that you were talking about?

https://www.nsa.gov/news-features/decla … 078762.pdf

Uploaded it for you

https://docs.zoho.com/file/9j5vv3dbaa85 … 52b691bd1c
(you may have to click download to view the pdf file)

Picked it up somewhere in 2016, look for the latter part where lists of patterns compared to words are listed on multiple pages. Looks like this (p. 3-29), left row is a patterns (A for the first unknown letter, B for the second etc.) and in the second line is an idea which word could match such pattern. They only used few words, of course – still a longer list – instead of a full dictionary.

What you see is actually an approach for monoalphabetic substitution. What was written above actually does the same, with the full dictionary all at once, on multiple positions and in addition to that considering the possibility of multiple homophones for each alphabetical letter. Then continue to combine it with the ‘+’ symbol and a 5-gram of (almost) free choice..

QT

Thanks a lot. It is the same one, which I have not read before. This will give me something new to read during my work breaks. Thanks again.

ABC DEF GFHIBJF.

QT

Good read going thru these posts,
Im very happy to see i came to some conclusions on my own that are much like yours.

A thought ive been playing with is that many symbols are actually determiners / adjectives.

For instance the zodiac symbol i suspected to be "T" or "H" then i thought it was "TH" which makes a bit of sense but it opens the door to the possibility of being "THE"

And in response to "+" being "L" i suggest that L20 #15 & #16 offers two clues,
A) theres no full stop, infering that the ending is maybe else where.
B)Its possibly a PS.
C)Or just filler

Goodluck and look forward to seeing more of your work.

To identify another symbol would be a great breakthrough…such as words with less frequent letters, e.g. ‘YOU’ or ‘HAVE’, which are likely to occur in a cipher text of that length. The question is: where?

QT

Z won’t be crack proof, nor will be his 340 cipher.

There – potentially – is a good way to crack his cipher. The following method should be able to crack a significant part of the 340 (assuming it is a homophone substitution cipher):

1. Set the + symbol (e.g. ‘S’ or ‘L’…frequent double letter)

2. Set the IoFBc combination in line 13 (e.g. ‘ENTER’, ‘THING’, ‘OFTHE’ etc.)

3. Set a bigram for the last two homophones in line 17.

4. Complete symbol #3 and symbol #6 of line 17 by using a (group of) 5-gram(s).

5. Complete symbols #7, #8, #9 of line 17 by using a second group of 5-grams on top of each 5-gram from step no. 4.

6. Independent from steps no. 4 and 5, complete the symbols #12 and #13 of line 17 by using a (separate) group of 5-grams.

And we will receive a (group of) strings of length 21 letters.

7. Search this string for at least 2, better 3 words of length >4 by using a dictionary (root words only, search with algorithm).

This method enables to not only search for one single letter or word, but to search for multiple words in a specific part of the cipher. To do so, the following components are used: Dictionary, word pattern matching, iteration/brute force, filling up with 5-grams.

The idea behind that procedure is the following: One may choose a letter for the + symbol, e.g. by using Bernoulli or any double letter from a double letter frequency table (the ‘++’ occurs three times). From then on, focussing on ‘frequent’ trigrams and bigrams for those n-grams which are indeed repeating in the 340 – simply because they indeed do occur at least twice in the cipher. Such step, for example, eliminates ‘XXXZZ’ for the IoFBc combination in line 13.

The rest is filled up. Now you can either iterate all alphabetical letters from A-Z, or, if there is already some letters present in a sequence of five letters in a row, look up some matching 5-grams in a 5-gram frequency table. There again, one may want to choose to only look into the most frequent one million different 5-grams instead of choosing all of the potentially thinkable 11 million 5-grams (again ‘spoken language’ instead of XXXZZ).

Most likely, for each + symbol and IoFBc combination, you end up at approximately 8 million different strings that can be searched for two, three or more words inside (each). That again is computable.

The question is, however, if there will be 2 or 3 words found in such 21-letter strings. I guess searching for two could lead to too many results out of e.g. 8 million different strings, while if 3 words are found that could indeed be interesting (71% ‘readable’ text in such a string).

Still a long way to go, however a solid approach – as long as there are nt statistical outliers amongst Z’s repeating tri- and bigrams.

QT

Currently using a similar method: Four different strings being searched for words from a dictionary. Now duplicates have been eliminated. Using approximately 13 different variables (letters, bigrams) for each 5-gram (‘IoFBc”; line 13). Those variables not all at once but step by step only if one word has already been found in the first, second, third etc. string.

Currently, the results look like this:

The program is still iterating letters in the 3rd and 4th string, with the first two strings still being the same. This changes over the time the more symbols will have been iterated through alphabetical letters. All potential solutions can be found this way, covering a total of 166 homophones or 48.8% of the cipher (cleartext), btw (with the rest possibly being completed manually). The program is working as it should, however there is a total of five loops nested into each other, which might be improved by different Python functions in the near future.

Nevertheless, we talk about potential Z cleartext popping up on the list.

QT

The double letter you are speaking of I believe is "SS" as He gave us this clue when he used it in the spelling of "christmass" in one of his letters
Respectfully
TGOZ

looking good quicktrader, i think you are on the right path.

Iteration of alphabets requires heavy computation..thus, I went back to the 16-letter string from line 17 (‘pFlWBIOLpp0WCZWc‘). Searching for at least two words of length >4 in that string, using a dictionary with ~4,500 words.

So far, besides learning to program ‘Python’ as well as creating a unique dictionary consisting of word roots only, some other troubles had occurred:

– ‘overlapping’ words (which is not a realistic finding of two words in the string)
– duplicates of results with iteration at non-relevant positions of the string

Both has been ‘solved’. Thus we now can get REAL CLEARTEXT variations for that specific 16-letter string.

Currently, all computation is based on a group of ‘frequent’ 5-grams for the ‘IoFBc‘ section (we have to make compromises..). Also, the + symbol was set (currently: ‘S’). By doing so, we can now compute specific runs for each ‘OL‘ bigram of the string, which is actually a repeating one. Checking one (rather frequent) of such bigrams after another. The results look somehow like the following list, here shown for the bigram ‘HI’.

We can ‘learn’ from the results:
For example that there is no (!) two words found in the 16-letter string for the 5-gram ‘ANDTH’ (for the IoFBc homophones) in combination with the bigram ‘HI’ (for the OL homophones). However, there is such result for e.g. ‘ETHER’ and ‘HI’.

Some of the results are even promising:

SOMONTHISSHORTOS
so month is short os

SEXACTHISSHAPEAO
s exact his shape ao

SEWORTHISSHOWNOE
se worth is shown oe

Whatsoever. One computation ‘run’ takes approximately 5-10 Minutes and covers about 870,000,000 different letter variations. It’s actually 131.6B but I decided to meanwhile let the W symbol being a ‘frequent’ letter (as it occurs 3x in that 16-letter string).

In this run, approximately 440 results out of those 870m variations showed up.

The idea is to continue computation with such results only.

QT

FCCP-List
THERE HI
SEEARTHISSHAREAE [{'Pos': 2, 'Word': 'earth'}, {'Pos': 9, 'Word': 'share'}]
SEEARTHISSHARPAE [{'Pos': 2, 'Word': 'earth'}, {'Pos': 9, 'Word': 'sharp'}]
SEEARTHISSHALTAE [{'Pos': 2, 'Word': 'earth'}, {'Pos': 9, 'Word': 'shalt'}]
SEEARTHISSHALLAE [{'Pos': 2, 'Word': 'earth'}, {'Pos': 9, 'Word': 'shall'}]
SEEARTHISSHADEAE [{'Pos': 2, 'Word': 'earth'}, {'Pos': 9, 'Word': 'shade'}]
SEEARTHISSHADYAE [{'Pos': 2, 'Word': 'earth'}, {'Pos': 9, 'Word': 'shady'}]
SEEARTHISSHAMEAE [{'Pos': 2, 'Word': 'earth'}, {'Pos': 9, 'Word': 'shame'}]
SEEARTHISSHAFTAE [{'Pos': 2, 'Word': 'earth'}, {'Pos': 9, 'Word': 'shaft'}]
SEEARTHISSHAPEAE [{'Pos': 2, 'Word': 'earth'}, {'Pos': 9, 'Word': 'shape'}]
SEEARTHISSHAWLAE [{'Pos': 2, 'Word': 'earth'}, {'Pos': 9, 'Word': 'shawl'}]
SEEARTHISSHAKEAE [{'Pos': 2, 'Word': 'earth'}, {'Pos': 9, 'Word': 'shake'}]
SENORTHISSHOESOE [{'Pos': 2, 'Word': 'north'}, {'Pos': 9, 'Word': 'shoes'}]
SENORTHISSHOOTOE [{'Pos': 2, 'Word': 'north'}, {'Pos': 9, 'Word': 'shoot'}]
SENORTHISSHOOKOE [{'Pos': 2, 'Word': 'north'}, {'Pos': 9, 'Word': 'shook'}]
SENORTHISSHONEOE [{'Pos': 2, 'Word': 'north'}, {'Pos': 9, 'Word': 'shone'}]
SENORTHISSHOREOE [{'Pos': 2, 'Word': 'north'}, {'Pos': 9, 'Word': 'shore'}]
SENORTHISSHORTOE [{'Pos': 2, 'Word': 'north'}, {'Pos': 9, 'Word': 'short'}]
SENORTHISSHOCKOE [{'Pos': 2, 'Word': 'north'}, {'Pos': 9, 'Word': 'shock'}]
SENORTHISSHOUTOE [{'Pos': 2, 'Word': 'north'}, {'Pos': 9, 'Word': 'shout'}]
SENORTHISSHOPSOE [{'Pos': 2, 'Word': 'north'}, {'Pos': 9, 'Word': 'shops'}]
SENORTHISSHOWNOE [{'Pos': 2, 'Word': 'north'}, {'Pos': 9, 'Word': 'shown'}]
SENORTHISSHOWSOE [{'Pos': 2, 'Word': 'north'}, {'Pos': 9, 'Word': 'shows'}]
SEMIRTHISSHINEIE [{'Pos': 2, 'Word': 'mirth'}, {'Pos': 9, 'Word': 'shine'}]
SEMIRTHISSHIRTIE [{'Pos': 2, 'Word': 'mirth'}, {'Pos': 9, 'Word': 'shirt'}]
SEMIRTHISSHIFTIE [{'Pos': 2, 'Word': 'mirth'}, {'Pos': 9, 'Word': 'shift'}]
SEMIRTHISSHIPSIE [{'Pos': 2, 'Word': 'mirth'}, {'Pos': 9, 'Word': 'ships'}]
SEFORTHISSHOESOE [{'Pos': 2, 'Word': 'forth'}, {'Pos': 9, 'Word': 'shoes'}]
SEFORTHISSHOOTOE [{'Pos': 2, 'Word': 'forth'}, {'Pos': 9, 'Word': 'shoot'}]
SEFORTHISSHOOKOE [{'Pos': 2, 'Word': 'forth'}, {'Pos': 9, 'Word': 'shook'}]
SEFORTHISSHONEOE [{'Pos': 2, 'Word': 'forth'}, {'Pos': 9, 'Word': 'shone'}]
SEFORTHISSHOREOE [{'Pos': 2, 'Word': 'forth'}, {'Pos': 9, 'Word': 'shore'}]
SEFORTHISSHORTOE [{'Pos': 2, 'Word': 'forth'}, {'Pos': 9, 'Word': 'short'}]
SEFORTHISSHOCKOE [{'Pos': 2, 'Word': 'forth'}, {'Pos': 9, 'Word': 'shock'}]
SEFORTHISSHOUTOE [{'Pos': 2, 'Word': 'forth'}, {'Pos': 9, 'Word': 'shout'}]
SEFORTHISSHOPSOE [{'Pos': 2, 'Word': 'forth'}, {'Pos': 9, 'Word': 'shops'}]
SEFORTHISSHOWNOE [{'Pos': 2, 'Word': 'forth'}, {'Pos': 9, 'Word': 'shown'}]
SEFORTHISSHOWSOE [{'Pos': 2, 'Word': 'forth'}, {'Pos': 9, 'Word': 'shows'}]
SEWORTHISSHOESOE [{'Pos': 2, 'Word': 'worth'}, {'Pos': 9, 'Word': 'shoes'}]
SEWORTHISSHOOTOE [{'Pos': 2, 'Word': 'worth'}, {'Pos': 9, 'Word': 'shoot'}]
SEWORTHISSHOOKOE [{'Pos': 2, 'Word': 'worth'}, {'Pos': 9, 'Word': 'shook'}]
SEWORTHISSHONEOE [{'Pos': 2, 'Word': 'worth'}, {'Pos': 9, 'Word': 'shone'}]
SEWORTHISSHOREOE [{'Pos': 2, 'Word': 'worth'}, {'Pos': 9, 'Word': 'shore'}]
SEWORTHISSHORTOE [{'Pos': 2, 'Word': 'worth'}, {'Pos': 9, 'Word': 'short'}]
SEWORTHISSHOCKOE [{'Pos': 2, 'Word': 'worth'}, {'Pos': 9, 'Word': 'shock'}]
SEWORTHISSHOUTOE [{'Pos': 2, 'Word': 'worth'}, {'Pos': 9, 'Word': 'shout'}]
SEWORTHISSHOPSOE [{'Pos': 2, 'Word': 'worth'}, {'Pos': 9, 'Word': 'shops'}]
SEWORTHISSHOWNOE [{'Pos': 2, 'Word': 'worth'}, {'Pos': 9, 'Word': 'shown'}]
SEWORTHISSHOWSOE [{'Pos': 2, 'Word': 'worth'}, {'Pos': 9, 'Word': 'shows'}]
SEBERTHISSHEETEE [{'Pos': 2, 'Word': 'berth'}, {'Pos': 9, 'Word': 'sheet'}]
SEBERTHISSHEEREE [{'Pos': 2, 'Word': 'berth'}, {'Pos': 9, 'Word': 'sheer'}]
SEBERTHISSHEEPEE [{'Pos': 2, 'Word': 'berth'}, {'Pos': 9, 'Word': 'sheep'}]
SEBERTHISSHEAVEE [{'Pos': 2, 'Word': 'berth'}, {'Pos': 10, 'Word': 'heave'}]
SEBERTHISSHENCEE [{'Pos': 2, 'Word': 'berth'}, {'Pos': 10, 'Word': 'hence'}]
SEBERTHISSHELLEE [{'Pos': 2, 'Word': 'berth'}, {'Pos': 9, 'Word': 'shell'}]
SEBERTHISSHELFEE [{'Pos': 2, 'Word': 'berth'}, {'Pos': 9, 'Word': 'shelf'}]
SEBERTHISSHEDGEE [{'Pos': 2, 'Word': 'berth'}, {'Pos': 10, 'Word': 'hedge'}]
SEBIRTHISSHINEIE [{'Pos': 2, 'Word': 'birth'}, {'Pos': 9, 'Word': 'shine'}]
SEBIRTHISSHIRTIE [{'Pos': 2, 'Word': 'birth'}, {'Pos': 9, 'Word': 'shirt'}]
SEBIRTHISSHIFTIE [{'Pos': 2, 'Word': 'birth'}, {'Pos': 9, 'Word': 'shift'}]
SEBIRTHISSHIPSIE [{'Pos': 2, 'Word': 'birth'}, {'Pos': 9, 'Word': 'ships'}]
SEXERTHISSHEETEE [{'Pos': 1, 'Word': 'exert'}, {'Pos': 9, 'Word': 'sheet'}]
SEXERTHISSHEEREE [{'Pos': 1, 'Word': 'exert'}, {'Pos': 9, 'Word': 'sheer'}]
SEXERTHISSHEEPEE [{'Pos': 1, 'Word': 'exert'}, {'Pos': 9, 'Word': 'sheep'}]
SEXERTHISSHEAVEE [{'Pos': 1, 'Word': 'exert'}, {'Pos': 10, 'Word': 'heave'}]
SEXERTHISSHENCEE [{'Pos': 1, 'Word': 'exert'}, {'Pos': 10, 'Word': 'hence'}]
SEXERTHISSHELLEE [{'Pos': 1, 'Word': 'exert'}, {'Pos': 9, 'Word': 'shell'}]
SEXERTHISSHELFEE [{'Pos': 1, 'Word': 'exert'}, {'Pos': 9, 'Word': 'shelf'}]
SEXERTHISSHEDGEE [{'Pos': 1, 'Word': 'exert'}, {'Pos': 10, 'Word': 'hedge'}]
ENTHE HI
ENTER HI
STAREEHISSHRUGRR [{'Pos': 0, 'Word': 'stare'}, {'Pos': 9, 'Word': 'shrug'}]
STOREEHISSHRUGRR [{'Pos': 0, 'Word': 'store'}, {'Pos': 9, 'Word': 'shrug'}]
STHREEHISSHRUGRR [{'Pos': 1, 'Word': 'three'}, {'Pos': 9, 'Word': 'shrug'}]
ERENT HI
SEVENEHISSHEETET [{'Pos': 0, 'Word': 'seven'}, {'Pos': 9, 'Word': 'sheet'}]
SEVENEHISSHEERET [{'Pos': 0, 'Word': 'seven'}, {'Pos': 9, 'Word': 'sheer'}]
SEVENEHISSHEEPET [{'Pos': 0, 'Word': 'seven'}, {'Pos': 9, 'Word': 'sheep'}]
SEVENEHISSHEAVET [{'Pos': 0, 'Word': 'seven'}, {'Pos': 10, 'Word': 'heave'}]
SEVENEHISSHENCET [{'Pos': 0, 'Word': 'seven'}, {'Pos': 10, 'Word': 'hence'}]
SEVENEHISSHELLET [{'Pos': 0, 'Word': 'seven'}, {'Pos': 9, 'Word': 'shell'}]
SEVENEHISSHELMET [{'Pos': 0, 'Word': 'seven'}, {'Pos': 10, 'Word': 'helmet'}]
SEVENEHISSHELFET [{'Pos': 0, 'Word': 'seven'}, {'Pos': 9, 'Word': 'shelf'}]
SEVENEHISSHEDGET [{'Pos': 0, 'Word': 'seven'}, {'Pos': 10, 'Word': 'hedge'}]
THAND HI
SATENTHISSHEETED [{'Pos': 2, 'Word': 'tenth'}, {'Pos': 9, 'Word': 'sheet'}]
SATENTHISSHEERED [{'Pos': 2, 'Word': 'tenth'}, {'Pos': 9, 'Word': 'sheer'}]
SATENTHISSHEEPED [{'Pos': 2, 'Word': 'tenth'}, {'Pos': 9, 'Word': 'sheep'}]
SATENTHISSHEATED [{'Pos': 2, 'Word': 'tenth'}, {'Pos': 10, 'Word': 'heated'}]
SATENTHISSHEADED [{'Pos': 2, 'Word': 'tenth'}, {'Pos': 10, 'Word': 'headed'}]
SATENTHISSHEAPED [{'Pos': 2, 'Word': 'tenth'}, {'Pos': 10, 'Word': 'heaped'}]
SATENTHISSHEAVED [{'Pos': 2, 'Word': 'tenth'}, {'Pos': 10, 'Word': 'heave'}]
SATENTHISSHENDED [{'Pos': 2, 'Word': 'tenth'}, {'Pos': 11, 'Word': 'ended'}]
SATENTHISSHENCED [{'Pos': 2, 'Word': 'tenth'}, {'Pos': 10, 'Word': 'hence'}]
SATENTHISSHELLED [{'Pos': 2, 'Word': 'tenth'}, {'Pos': 9, 'Word': 'shell'}]
SATENTHISSHELFED [{'Pos': 2, 'Word': 'tenth'}, {'Pos': 9, 'Word': 'shelf'}]
SATENTHISSHELPED [{'Pos': 2, 'Word': 'tenth'}, {'Pos': 10, 'Word': 'helped'}]
SATENTHISSHEDGED [{'Pos': 2, 'Word': 'tenth'}, {'Pos': 10, 'Word': 'hedge'}]
SATANTHISSHAREAD [{'Pos': 0, 'Word': 'satan'}, {'Pos': 9, 'Word': 'share'}]
SATANTHISSHARPAD [{'Pos': 0, 'Word': 'satan'}, {'Pos': 9, 'Word': 'sharp'}]
SATANTHISSHAHEAD [{'Pos': 0, 'Word': 'satan'}, {'Pos': 11, 'Word': 'ahead'}]
SATANTHISSHALTAD [{'Pos': 0, 'Word': 'satan'}, {'Pos': 9, 'Word': 'shalt'}]
SATANTHISSHALLAD [{'Pos': 0, 'Word': 'satan'}, {'Pos': 9, 'Word': 'shall'}]
SATANTHISSHADEAD [{'Pos': 0, 'Word': 'satan'}, {'Pos': 9, 'Word': 'shade'}]
SATANTHISSHADYAD [{'Pos': 0, 'Word': 'satan'}, {'Pos': 9, 'Word': 'shady'}]
SATANTHISSHAMEAD [{'Pos': 0, 'Word': 'satan'}, {'Pos': 9, 'Word': 'shame'}]
SATANTHISSHAFTAD [{'Pos': 0, 'Word': 'satan'}, {'Pos': 9, 'Word': 'shaft'}]
SATANTHISSHAPEAD [{'Pos': 0, 'Word': 'satan'}, {'Pos': 9, 'Word': 'shape'}]
SATANTHISSHAWLAD [{'Pos': 0, 'Word': 'satan'}, {'Pos': 9, 'Word': 'shawl'}]
SATANTHISSHAKEAD [{'Pos': 0, 'Word': 'satan'}, {'Pos': 9, 'Word': 'shake'}]
SATINTHISSHINEID [{'Pos': 0, 'Word': 'satin'}, {'Pos': 9, 'Word': 'shine'}]
SATINTHISSHIRTID [{'Pos': 0, 'Word': 'satin'}, {'Pos': 9, 'Word': 'shirt'}]
SATINTHISSHIFTID [{'Pos': 0, 'Word': 'satin'}, {'Pos': 9, 'Word': 'shift'}]
SATINTHISSHIPSID [{'Pos': 0, 'Word': 'satin'}, {'Pos': 9, 'Word': 'ships'}]
SANINTHISSHINEID [{'Pos': 2, 'Word': 'ninth'}, {'Pos': 9, 'Word': 'shine'}]
SANINTHISSHIRTID [{'Pos': 2, 'Word': 'ninth'}, {'Pos': 9, 'Word': 'shirt'}]
SANINTHISSHIFTID [{'Pos': 2, 'Word': 'ninth'}, {'Pos': 9, 'Word': 'shift'}]
SANINTHISSHIPSID [{'Pos': 2, 'Word': 'ninth'}, {'Pos': 9, 'Word': 'ships'}]
SARENTHISSHEETED [{'Pos': 1, 'Word': 'arent'}, {'Pos': 9, 'Word': 'sheet'}]
SARENTHISSHEERED [{'Pos': 1, 'Word': 'arent'}, {'Pos': 9, 'Word': 'sheer'}]
SARENTHISSHEEPED [{'Pos': 1, 'Word': 'arent'}, {'Pos': 9, 'Word': 'sheep'}]
SARENTHISSHEATED [{'Pos': 1, 'Word': 'arent'}, {'Pos': 10, 'Word': 'heated'}]
SARENTHISSHEADED [{'Pos': 1, 'Word': 'arent'}, {'Pos': 10, 'Word': 'headed'}]
SARENTHISSHEAPED [{'Pos': 1, 'Word': 'arent'}, {'Pos': 10, 'Word': 'heaped'}]
SARENTHISSHEAVED [{'Pos': 1, 'Word': 'arent'}, {'Pos': 10, 'Word': 'heave'}]
SARENTHISSHENDED [{'Pos': 1, 'Word': 'arent'}, {'Pos': 11, 'Word': 'ended'}]
SARENTHISSHENCED [{'Pos': 1, 'Word': 'arent'}, {'Pos': 10, 'Word': 'hence'}]
SARENTHISSHELLED [{'Pos': 1, 'Word': 'arent'}, {'Pos': 9, 'Word': 'shell'}]
SARENTHISSHELFED [{'Pos': 1, 'Word': 'arent'}, {'Pos': 9, 'Word': 'shelf'}]
SARENTHISSHELPED [{'Pos': 1, 'Word': 'arent'}, {'Pos': 10, 'Word': 'helped'}]
SARENTHISSHEDGED [{'Pos': 1, 'Word': 'arent'}, {'Pos': 10, 'Word': 'hedge'}]
SALONTHISSHOESOD [{'Pos': 0, 'Word': 'salon'}, {'Pos': 9, 'Word': 'shoes'}]
SALONTHISSHOOTOD [{'Pos': 0, 'Word': 'salon'}, {'Pos': 9, 'Word': 'shoot'}]
SALONTHISSHOOKOD [{'Pos': 0, 'Word': 'salon'}, {'Pos': 9, 'Word': 'shook'}]
SALONTHISSHONEOD [{'Pos': 0, 'Word': 'salon'}, {'Pos': 9, 'Word': 'shone'}]
SALONTHISSHOREOD [{'Pos': 0, 'Word': 'salon'}, {'Pos': 9, 'Word': 'shore'}]
SALONTHISSHORTOD [{'Pos': 0, 'Word': 'salon'}, {'Pos': 9, 'Word': 'short'}]
SALONTHISSHOCKOD [{'Pos': 0, 'Word': 'salon'}, {'Pos': 9, 'Word': 'shock'}]
SALONTHISSHOUTOD [{'Pos': 0, 'Word': 'salon'}, {'Pos': 9, 'Word': 'shout'}]
SALONTHISSHOPSOD [{'Pos': 0, 'Word': 'salon'}, {'Pos': 9, 'Word': 'shops'}]
SALONTHISSHOWNOD [{'Pos': 0, 'Word': 'salon'}, {'Pos': 9, 'Word': 'shown'}]
SALONTHISSHOWSOD [{'Pos': 0, 'Word': 'salon'}, {'Pos': 9, 'Word': 'shows'}]
SAMONTHISSHOESOD [{'Pos': 2, 'Word': 'month'}, {'Pos': 9, 'Word': 'shoes'}]
SAMONTHISSHOOTOD [{'Pos': 2, 'Word': 'month'}, {'Pos': 9, 'Word': 'shoot'}]
SAMONTHISSHOOKOD [{'Pos': 2, 'Word': 'month'}, {'Pos': 9, 'Word': 'shook'}]
SAMONTHISSHONEOD [{'Pos': 2, 'Word': 'month'}, {'Pos': 9, 'Word': 'shone'}]
SAMONTHISSHOREOD [{'Pos': 2, 'Word': 'month'}, {'Pos': 9, 'Word': 'shore'}]
SAMONTHISSHORTOD [{'Pos': 2, 'Word': 'month'}, {'Pos': 9, 'Word': 'short'}]
SAMONTHISSHOCKOD [{'Pos': 2, 'Word': 'month'}, {'Pos': 9, 'Word': 'shock'}]
SAMONTHISSHOUTOD [{'Pos': 2, 'Word': 'month'}, {'Pos': 9, 'Word': 'shout'}]
SAMONTHISSHOPSOD [{'Pos': 2, 'Word': 'month'}, {'Pos': 9, 'Word': 'shops'}]
SAMONTHISSHOWNOD [{'Pos': 2, 'Word': 'month'}, {'Pos': 9, 'Word': 'shown'}]
SAMONTHISSHOWSOD [{'Pos': 2, 'Word': 'month'}, {'Pos': 9, 'Word': 'shows'}]
SAGENTHISSHEETED [{'Pos': 1, 'Word': 'agent'}, {'Pos': 9, 'Word': 'sheet'}]
SAGENTHISSHEERED [{'Pos': 1, 'Word': 'agent'}, {'Pos': 9, 'Word': 'sheer'}]
SAGENTHISSHEEPED [{'Pos': 1, 'Word': 'agent'}, {'Pos': 9, 'Word': 'sheep'}]
SAGENTHISSHEATED [{'Pos': 1, 'Word': 'agent'}, {'Pos': 10, 'Word': 'heated'}]
SAGENTHISSHEADED [{'Pos': 1, 'Word': 'agent'}, {'Pos': 10, 'Word': 'headed'}]
SAGENTHISSHEAPED [{'Pos': 1, 'Word': 'agent'}, {'Pos': 10, 'Word': 'heaped'}]
SAGENTHISSHEAVED [{'Pos': 1, 'Word': 'agent'}, {'Pos': 10, 'Word': 'heave'}]
SAGENTHISSHENDED [{'Pos': 1, 'Word': 'agent'}, {'Pos': 11, 'Word': 'ended'}]
SAGENTHISSHENCED [{'Pos': 1, 'Word': 'agent'}, {'Pos': 10, 'Word': 'hence'}]
SAGENTHISSHELLED [{'Pos': 1, 'Word': 'agent'}, {'Pos': 9, 'Word': 'shell'}]
SAGENTHISSHELFED [{'Pos': 1, 'Word': 'agent'}, {'Pos': 9, 'Word': 'shelf'}]
SAGENTHISSHELPED [{'Pos': 1, 'Word': 'agent'}, {'Pos': 10, 'Word': 'helped'}]
SAGENTHISSHEDGED [{'Pos': 1, 'Word': 'agent'}, {'Pos': 10, 'Word': 'hedge'}]
HATHE HI
HATHA HI
ENTHA HI
THENT HI
SETENTHISSHEETET [{'Pos': 2, 'Word': 'tenth'}, {'Pos': 9, 'Word': 'sheet'}]
SETENTHISSHEERET [{'Pos': 2, 'Word': 'tenth'}, {'Pos': 9, 'Word': 'sheer'}]
SETENTHISSHEEPET [{'Pos': 2, 'Word': 'tenth'}, {'Pos': 9, 'Word': 'sheep'}]
SETENTHISSHEAVET [{'Pos': 2, 'Word': 'tenth'}, {'Pos': 10, 'Word': 'heave'}]
SETENTHISSHENCET [{'Pos': 2, 'Word': 'tenth'}, {'Pos': 10, 'Word': 'hence'}]
SETENTHISSHELLET [{'Pos': 2, 'Word': 'tenth'}, {'Pos': 9, 'Word': 'shell'}]
SETENTHISSHELMET [{'Pos': 2, 'Word': 'tenth'}, {'Pos': 10, 'Word': 'helmet'}]
SETENTHISSHELFET [{'Pos': 2, 'Word': 'tenth'}, {'Pos': 9, 'Word': 'shelf'}]
SETENTHISSHEDGET [{'Pos': 2, 'Word': 'tenth'}, {'Pos': 10, 'Word': 'hedge'}]
SENINTHISSHINEIT [{'Pos': 2, 'Word': 'ninth'}, {'Pos': 9, 'Word': 'shine'}]
SENINTHISSHIRTIT [{'Pos': 2, 'Word': 'ninth'}, {'Pos': 9, 'Word': 'shirt'}]
SENINTHISSHIFTIT [{'Pos': 2, 'Word': 'ninth'}, {'Pos': 9, 'Word': 'shift'}]
SENINTHISSHIPSIT [{'Pos': 2, 'Word': 'ninth'}, {'Pos': 9, 'Word': 'ships'}]
SEMONTHISSHOESOT [{'Pos': 2, 'Word': 'month'}, {'Pos': 9, 'Word': 'shoes'}]
SEMONTHISSHOOTOT [{'Pos': 2, 'Word': 'month'}, {'Pos': 9, 'Word': 'shoot'}]
SEMONTHISSHOOKOT [{'Pos': 2, 'Word': 'month'}, {'Pos': 9, 'Word': 'shook'}]
SEMONTHISSHONEOT [{'Pos': 2, 'Word': 'month'}, {'Pos': 9, 'Word': 'shone'}]
SEMONTHISSHOREOT [{'Pos': 2, 'Word': 'month'}, {'Pos': 9, 'Word': 'shore'}]
SEMONTHISSHORTOT [{'Pos': 2, 'Word': 'month'}, {'Pos': 9, 'Word': 'short'}]
SEMONTHISSHOCKOT [{'Pos': 2, 'Word': 'month'}, {'Pos': 9, 'Word': 'shock'}]
SEMONTHISSHOUTOT [{'Pos': 2, 'Word': 'month'}, {'Pos': 9, 'Word': 'shout'}]
SEMONTHISSHOPSOT [{'Pos': 2, 'Word': 'month'}, {'Pos': 9, 'Word': 'shops'}]
SEMONTHISSHOWNOT [{'Pos': 2, 'Word': 'month'}, {'Pos': 9, 'Word': 'shown'}]
SEMONTHISSHOWSOT [{'Pos': 2, 'Word': 'month'}, {'Pos': 9, 'Word': 'shows'}]
ERERE HI
SEVEREHISSHEETEE [{'Pos': 0, 'Word': 'severe'}, {'Pos': 9, 'Word': 'sheet'}]
SEVEREHISSHEEREE [{'Pos': 0, 'Word': 'severe'}, {'Pos': 9, 'Word': 'sheer'}]
SEVEREHISSHEEPEE [{'Pos': 0, 'Word': 'severe'}, {'Pos': 9, 'Word': 'sheep'}]
SEVEREHISSHEAVEE [{'Pos': 0, 'Word': 'severe'}, {'Pos': 10, 'Word': 'heave'}]
SEVEREHISSHENCEE [{'Pos': 0, 'Word': 'severe'}, {'Pos': 10, 'Word': 'hence'}]
SEVEREHISSHELLEE [{'Pos': 0, 'Word': 'severe'}, {'Pos': 9, 'Word': 'shell'}]
SEVEREHISSHELFEE [{'Pos': 0, 'Word': 'severe'}, {'Pos': 9, 'Word': 'shelf'}]
SEVEREHISSHEDGEE [{'Pos': 0, 'Word': 'severe'}, {'Pos': 10, 'Word': 'hedge'}]
HATER HI
STAREHHISSHRUGRR [{'Pos': 0, 'Word': 'stare'}, {'Pos': 9, 'Word': 'shrug'}]
STOREHHISSHRUGRR [{'Pos': 0, 'Word': 'store'}, {'Pos': 9, 'Word': 'shrug'}]
THING HI
SITENTHISSHEETEG [{'Pos': 2, 'Word': 'tenth'}, {'Pos': 9, 'Word': 'sheet'}]
SITENTHISSHEEREG [{'Pos': 2, 'Word': 'tenth'}, {'Pos': 9, 'Word': 'sheer'}]
SITENTHISSHEEPEG [{'Pos': 2, 'Word': 'tenth'}, {'Pos': 9, 'Word': 'sheep'}]
SITENTHISSHEAVEG [{'Pos': 2, 'Word': 'tenth'}, {'Pos': 10, 'Word': 'heave'}]
SITENTHISSHENCEG [{'Pos': 2, 'Word': 'tenth'}, {'Pos': 10, 'Word': 'hence'}]
SITENTHISSHELLEG [{'Pos': 2, 'Word': 'tenth'}, {'Pos': 9, 'Word': 'shell'}]
SITENTHISSHELFEG [{'Pos': 2, 'Word': 'tenth'}, {'Pos': 9, 'Word': 'shelf'}]
SITENTHISSHEDGEG [{'Pos': 2, 'Word': 'tenth'}, {'Pos': 10, 'Word': 'hedge'}]
SININTHISSHINEIG [{'Pos': 2, 'Word': 'ninth'}, {'Pos': 9, 'Word': 'shine'}]
SININTHISSHIRTIG [{'Pos': 2, 'Word': 'ninth'}, {'Pos': 9, 'Word': 'shirt'}]
SININTHISSHIFTIG [{'Pos': 2, 'Word': 'ninth'}, {'Pos': 9, 'Word': 'shift'}]
SININTHISSHIPSIG [{'Pos': 2, 'Word': 'ninth'}, {'Pos': 9, 'Word': 'ships'}]
SILENTHISSHEETEG [{'Pos': 0, 'Word': 'silent'}, {'Pos': 9, 'Word': 'sheet'}]
SILENTHISSHEEREG [{'Pos': 0, 'Word': 'silent'}, {'Pos': 9, 'Word': 'sheer'}]
SILENTHISSHEEPEG [{'Pos': 0, 'Word': 'silent'}, {'Pos': 9, 'Word': 'sheep'}]
SILENTHISSHEAVEG [{'Pos': 0, 'Word': 'silent'}, {'Pos': 10, 'Word': 'heave'}]
SILENTHISSHENCEG [{'Pos': 0, 'Word': 'silent'}, {'Pos': 10, 'Word': 'hence'}]
SILENTHISSHELLEG [{'Pos': 0, 'Word': 'silent'}, {'Pos': 9, 'Word': 'shell'}]
SILENTHISSHELFEG [{'Pos': 0, 'Word': 'silent'}, {'Pos': 9, 'Word': 'shelf'}]
SILENTHISSHEDGEG [{'Pos': 0, 'Word': 'silent'}, {'Pos': 10, 'Word': 'hedge'}]
SIMONTHISSHOESOG [{'Pos': 2, 'Word': 'month'}, {'Pos': 9, 'Word': 'shoes'}]
SIMONTHISSHOOTOG [{'Pos': 2, 'Word': 'month'}, {'Pos': 9, 'Word': 'shoot'}]
SIMONTHISSHOOKOG [{'Pos': 2, 'Word': 'month'}, {'Pos': 9, 'Word': 'shook'}]
SIMONTHISSHONEOG [{'Pos': 2, 'Word': 'month'}, {'Pos': 9, 'Word': 'shone'}]
SIMONTHISSHOREOG [{'Pos': 2, 'Word': 'month'}, {'Pos': 9, 'Word': 'shore'}]
SIMONTHISSHORTOG [{'Pos': 2, 'Word': 'month'}, {'Pos': 9, 'Word': 'short'}]
SIMONTHISSHOCKOG [{'Pos': 2, 'Word': 'month'}, {'Pos': 9, 'Word': 'shock'}]
SIMONTHISSHOUTOG [{'Pos': 2, 'Word': 'month'}, {'Pos': 9, 'Word': 'shout'}]
SIMONTHISSHOPSOG [{'Pos': 2, 'Word': 'month'}, {'Pos': 9, 'Word': 'shops'}]
SIMONTHISSHOWNOG [{'Pos': 2, 'Word': 'month'}, {'Pos': 9, 'Word': 'shown'}]
SIMONTHISSHOWSOG [{'Pos': 2, 'Word': 'month'}, {'Pos': 9, 'Word': 'shows'}]
WITHA HI
WITHI HI
ITHER HI
SHAREIHISSHRUGRR [{'Pos': 0, 'Word': 'share'}, {'Pos': 9, 'Word': 'shrug'}]
SHOREIHISSHRUGRR [{'Pos': 0, 'Word': 'shore'}, {'Pos': 9, 'Word': 'shrug'}]
WITHE HI
ENTHI HI
ITHAT HI
THALL HI
SAFILTHISSHINEIL [{'Pos': 2, 'Word': 'filth'}, {'Pos': 9, 'Word': 'shine'}]
SAFILTHISSHIRTIL [{'Pos': 2, 'Word': 'filth'}, {'Pos': 9, 'Word': 'shirt'}]
SAFILTHISSHIFTIL [{'Pos': 2, 'Word': 'filth'}, {'Pos': 9, 'Word': 'shift'}]
SAFILTHISSHIPSIL [{'Pos': 2, 'Word': 'filth'}, {'Pos': 9, 'Word': 'ships'}]
HATHI HI
ITHIS HI
THITH HI
OFTHE HI
ATION HI
INGTH HI
OTHER HI
SHAREOHISSHRUGRR [{'Pos': 0, 'Word': 'share'}, {'Pos': 9, 'Word': 'shrug'}]
SHOREOHISSHRUGRR [{'Pos': 0, 'Word': 'shore'}, {'Pos': 9, 'Word': 'shrug'}]
ANDTH HI
ETHAT HI
DTHAT HI
ETHER HI
SHAREEHISSHRUGRR [{'Pos': 0, 'Word': 'share'}, {'Pos': 9, 'Word': 'shrug'}]
SHOREEHISSHRUGRR [{'Pos': 0, 'Word': 'shore'}, {'Pos': 9, 'Word': 'shrug'}]
NTHIS HI
NTHER HI
SHARENHISSHRUGRR [{'Pos': 0, 'Word': 'share'}, {'Pos': 9, 'Word': 'shrug'}]
SHORENHISSHRUGRR [{'Pos': 0, 'Word': 'shore'}, {'Pos': 9, 'Word': 'shrug'}]
NTHAT HI
ETHIS HI
DTHER HI
SHAREDHISSHRUGRR [{'Pos': 0, 'Word': 'share'}, {'Pos': 9, 'Word': 'shrug'}]
SHOREDHISSHRUGRR [{'Pos': 0, 'Word': 'shore'}, {'Pos': 9, 'Word': 'shrug'}]
SHIREDHISSHRUGRR [{'Pos': 1, 'Word': 'hired'}, {'Pos': 9, 'Word': 'shrug'}]
THETH HI
ERETH HI
SENATEHISSHAREAH [{'Pos': 0, 'Word': 'senate'}, {'Pos': 9, 'Word': 'share'}]
SENATEHISSHARPAH [{'Pos': 0, 'Word': 'senate'}, {'Pos': 9, 'Word': 'sharp'}]
SENATEHISSHALTAH [{'Pos': 0, 'Word': 'senate'}, {'Pos': 9, 'Word': 'shalt'}]
SENATEHISSHALLAH [{'Pos': 0, 'Word': 'senate'}, {'Pos': 9, 'Word': 'shall'}]
SENATEHISSHADEAH [{'Pos': 0, 'Word': 'senate'}, {'Pos': 9, 'Word': 'shade'}]
SENATEHISSHADYAH [{'Pos': 0, 'Word': 'senate'}, {'Pos': 9, 'Word': 'shady'}]
SENATEHISSHAMEAH [{'Pos': 0, 'Word': 'senate'}, {'Pos': 9, 'Word': 'shame'}]
SENATEHISSHAFTAH [{'Pos': 0, 'Word': 'senate'}, {'Pos': 9, 'Word': 'shaft'}]
SENATEHISSHAPEAH [{'Pos': 0, 'Word': 'senate'}, {'Pos': 9, 'Word': 'shape'}]
SENATEHISSHAWLAH [{'Pos': 0, 'Word': 'senate'}, {'Pos': 9, 'Word': 'shawl'}]
SENATEHISSHAKEAH [{'Pos': 0, 'Word': 'senate'}, {'Pos': 9, 'Word': 'shake'}]
DTHIS HI
SHERE HI
SEHARSHISSHAREAE [{'Pos': 2, 'Word': 'harsh'}, {'Pos': 9, 'Word': 'share'}]
SEHARSHISSHARPAE [{'Pos': 2, 'Word': 'harsh'}, {'Pos': 9, 'Word': 'sharp'}]
SEHARSHISSHALTAE [{'Pos': 2, 'Word': 'harsh'}, {'Pos': 9, 'Word': 'shalt'}]
SEHARSHISSHALLAE [{'Pos': 2, 'Word': 'harsh'}, {'Pos': 9, 'Word': 'shall'}]
SEHARSHISSHADEAE [{'Pos': 2, 'Word': 'harsh'}, {'Pos': 9, 'Word': 'shade'}]
SEHARSHISSHADYAE [{'Pos': 2, 'Word': 'harsh'}, {'Pos': 9, 'Word': 'shady'}]
SEHARSHISSHAMEAE [{'Pos': 2, 'Word': 'harsh'}, {'Pos': 9, 'Word': 'shame'}]
SEHARSHISSHAFTAE [{'Pos': 2, 'Word': 'harsh'}, {'Pos': 9, 'Word': 'shaft'}]
SEHARSHISSHAPEAE [{'Pos': 2, 'Word': 'harsh'}, {'Pos': 9, 'Word': 'shape'}]
SEHARSHISSHAWLAE [{'Pos': 2, 'Word': 'harsh'}, {'Pos': 9, 'Word': 'shawl'}]
SEHARSHISSHAKEAE [{'Pos': 2, 'Word': 'harsh'}, {'Pos': 9, 'Word': 'shake'}]
SEMARSHISSHAREAE [{'Pos': 2, 'Word': 'marsh'}, {'Pos': 9, 'Word': 'share'}]
SEMARSHISSHARPAE [{'Pos': 2, 'Word': 'marsh'}, {'Pos': 9, 'Word': 'sharp'}]
SEMARSHISSHALTAE [{'Pos': 2, 'Word': 'marsh'}, {'Pos': 9, 'Word': 'shalt'}]
SEMARSHISSHALLAE [{'Pos': 2, 'Word': 'marsh'}, {'Pos': 9, 'Word': 'shall'}]
SEMARSHISSHADEAE [{'Pos': 2, 'Word': 'marsh'}, {'Pos': 9, 'Word': 'shade'}]
SEMARSHISSHADYAE [{'Pos': 2, 'Word': 'marsh'}, {'Pos': 9, 'Word': 'shady'}]
SEMARSHISSHAMEAE [{'Pos': 2, 'Word': 'marsh'}, {'Pos': 9, 'Word': 'shame'}]
SEMARSHISSHAFTAE [{'Pos': 2, 'Word': 'marsh'}, {'Pos': 9, 'Word': 'shaft'}]
SEMARSHISSHAPEAE [{'Pos': 2, 'Word': 'marsh'}, {'Pos': 9, 'Word': 'shape'}]
SEMARSHISSHAWLAE [{'Pos': 2, 'Word': 'marsh'}, {'Pos': 9, 'Word': 'shawl'}]
SEMARSHISSHAKEAE [{'Pos': 2, 'Word': 'marsh'}, {'Pos': 9, 'Word': 'shake'}]
HISHE HI
SHETH HI
TIONS HI
SOTENTHISSHEETES [{'Pos': 2, 'Word': 'tenth'}, {'Pos': 9, 'Word': 'sheet'}]
SOTENTHISSHEERES [{'Pos': 2, 'Word': 'tenth'}, {'Pos': 9, 'Word': 'sheer'}]
SOTENTHISSHEEPES [{'Pos': 2, 'Word': 'tenth'}, {'Pos': 9, 'Word': 'sheep'}]
SOTENTHISSHEAVES [{'Pos': 2, 'Word': 'tenth'}, {'Pos': 10, 'Word': 'heave'}]
SOTENTHISSHENCES [{'Pos': 2, 'Word': 'tenth'}, {'Pos': 10, 'Word': 'hence'}]
SOTENTHISSHEROES [{'Pos': 2, 'Word': 'tenth'}, {'Pos': 10, 'Word': 'heroes'}]
SOTENTHISSHELLES [{'Pos': 2, 'Word': 'tenth'}, {'Pos': 9, 'Word': 'shell'}]
SOTENTHISSHELFES [{'Pos': 2, 'Word': 'tenth'}, {'Pos': 9, 'Word': 'shelf'}]
SOTENTHISSHELVES [{'Pos': 2, 'Word': 'tenth'}, {'Pos': 9, 'Word': 'shelves'}]
SOTENTHISSHEDGES [{'Pos': 2, 'Word': 'tenth'}, {'Pos': 10, 'Word': 'hedge'}, {'Pos': 11, 'Word': 'edges'}]
SONINTHISSHINEIS [{'Pos': 2, 'Word': 'ninth'}, {'Pos': 9, 'Word': 'shine'}]
SONINTHISSHIRTIS [{'Pos': 2, 'Word': 'ninth'}, {'Pos': 9, 'Word': 'shirt'}]
SONINTHISSHIFTIS [{'Pos': 2, 'Word': 'ninth'}, {'Pos': 9, 'Word': 'shift'}]
SONINTHISSHIPSIS [{'Pos': 2, 'Word': 'ninth'}, {'Pos': 9, 'Word': 'ships'}]
SOMONTHISSHOESOS [{'Pos': 2, 'Word': 'month'}, {'Pos': 9, 'Word': 'shoes'}]
SOMONTHISSHOOTOS [{'Pos': 2, 'Word': 'month'}, {'Pos': 9, 'Word': 'shoot'}]
SOMONTHISSHOOKOS [{'Pos': 2, 'Word': 'month'}, {'Pos': 9, 'Word': 'shook'}]
SOMONTHISSHONEOS [{'Pos': 2, 'Word': 'month'}, {'Pos': 9, 'Word': 'shone'}]
SOMONTHISSHOREOS [{'Pos': 2, 'Word': 'month'}, {'Pos': 9, 'Word': 'shore'}]
SOMONTHISSHORTOS [{'Pos': 2, 'Word': 'month'}, {'Pos': 9, 'Word': 'short'}]
SOMONTHISSHOCKOS [{'Pos': 2, 'Word': 'month'}, {'Pos': 9, 'Word': 'shock'}]
SOMONTHISSHOUTOS [{'Pos': 2, 'Word': 'month'}, {'Pos': 9, 'Word': 'shout'}]
SOMONTHISSHOPSOS [{'Pos': 2, 'Word': 'month'}, {'Pos': 9, 'Word': 'shops'}]
SOMONTHISSHOWNOS [{'Pos': 2, 'Word': 'month'}, {'Pos': 9, 'Word': 'shown'}]
SOMONTHISSHOWSOS [{'Pos': 2, 'Word': 'month'}, {'Pos': 9, 'Word': 'shows'}]
NGTHE HI
INTHE HI
TOTHE HI
ATTHE HI
NDTHE HI
ONTHE HI
EDTHE HI
THEIR HI
SEFAITHISSHAREAR [{'Pos': 2, 'Word': 'faith'}, {'Pos': 9, 'Word': 'share'}]
SEFAITHISSHARPAR [{'Pos': 2, 'Word': 'faith'}, {'Pos': 9, 'Word': 'sharp'}]
SEFAITHISSHALTAR [{'Pos': 2, 'Word': 'faith'}, {'Pos': 9, 'Word': 'shalt'}, {'Pos': 11, 'Word': 'altar'}]
SEFAITHISSHALLAR [{'Pos': 2, 'Word': 'faith'}, {'Pos': 9, 'Word': 'shall'}]
SEFAITHISSHADEAR [{'Pos': 2, 'Word': 'faith'}, {'Pos': 9, 'Word': 'shade'}]
SEFAITHISSHADYAR [{'Pos': 2, 'Word': 'faith'}, {'Pos': 9, 'Word': 'shady'}]
SEFAITHISSHAMEAR [{'Pos': 2, 'Word': 'faith'}, {'Pos': 9, 'Word': 'shame'}]
SEFAITHISSHAFTAR [{'Pos': 2, 'Word': 'faith'}, {'Pos': 9, 'Word': 'shaft'}]
SEFAITHISSHAPEAR [{'Pos': 2, 'Word': 'faith'}, {'Pos': 9, 'Word': 'shape'}]
SEFAITHISSHAWLAR [{'Pos': 2, 'Word': 'faith'}, {'Pos': 9, 'Word': 'shawl'}]
SEFAITHISSHAKEAR [{'Pos': 2, 'Word': 'faith'}, {'Pos': 9, 'Word': 'shake'}]
TIONA HI
SOTENTHISSHEETEA [{'Pos': 2, 'Word': 'tenth'}, {'Pos': 9, 'Word': 'sheet'}]
SOTENTHISSHEEREA [{'Pos': 2, 'Word': 'tenth'}, {'Pos': 9, 'Word': 'sheer'}]
SOTENTHISSHEEPEA [{'Pos': 2, 'Word': 'tenth'}, {'Pos': 9, 'Word': 'sheep'}]
SOTENTHISSHEAVEA [{'Pos': 2, 'Word': 'tenth'}, {'Pos': 10, 'Word': 'heave'}]
SOTENTHISSHENCEA [{'Pos': 2, 'Word': 'tenth'}, {'Pos': 10, 'Word': 'hence'}]
SOTENTHISSHELLEA [{'Pos': 2, 'Word': 'tenth'}, {'Pos': 9, 'Word': 'shell'}]
SOTENTHISSHELFEA [{'Pos': 2, 'Word': 'tenth'}, {'Pos': 9, 'Word': 'shelf'}]
SOTENTHISSHEDGEA [{'Pos': 2, 'Word': 'tenth'}, {'Pos': 10, 'Word': 'hedge'}]
SONINTHISSHINEIA [{'Pos': 2, 'Word': 'ninth'}, {'Pos': 9, 'Word': 'shine'}]
SONINTHISSHIRTIA [{'Pos': 2, 'Word': 'ninth'}, {'Pos': 9, 'Word': 'shirt'}]
SONINTHISSHIFTIA [{'Pos': 2, 'Word': 'ninth'}, {'Pos': 9, 'Word': 'shift'}]
SONINTHISSHIPSIA [{'Pos': 2, 'Word': 'ninth'}, {'Pos': 9, 'Word': 'ships'}]
SOMONTHISSHOESOA [{'Pos': 2, 'Word': 'month'}, {'Pos': 9, 'Word': 'shoes'}]
SOMONTHISSHOOTOA [{'Pos': 2, 'Word': 'month'}, {'Pos': 9, 'Word': 'shoot'}]
SOMONTHISSHOOKOA [{'Pos': 2, 'Word': 'month'}, {'Pos': 9, 'Word': 'shook'}]
SOMONTHISSHONEOA [{'Pos': 2, 'Word': 'month'}, {'Pos': 9, 'Word': 'shone'}]
SOMONTHISSHOREOA [{'Pos': 2, 'Word': 'month'}, {'Pos': 9, 'Word': 'shore'}]
SOMONTHISSHORTOA [{'Pos': 2, 'Word': 'month'}, {'Pos': 9, 'Word': 'short'}]
SOMONTHISSHOCKOA [{'Pos': 2, 'Word': 'month'}, {'Pos': 9, 'Word': 'shock'}]
SOMONTHISSHOUTOA [{'Pos': 2, 'Word': 'month'}, {'Pos': 9, 'Word': 'shout'}]
SOMONTHISSHOPSOA [{'Pos': 2, 'Word': 'month'}, {'Pos': 9, 'Word': 'shops'}]
SOMONTHISSHOWNOA [{'Pos': 2, 'Word': 'month'}, {'Pos': 9, 'Word': 'shown'}]
SOMONTHISSHOWSOA [{'Pos': 2, 'Word': 'month'}, {'Pos': 9, 'Word': 'shows'}]
ORTHE HI
FORTH HI
INGTO HI
THECO HI
SERECTHISSHEETEO [{'Pos': 1, 'Word': 'erect'}, {'Pos': 9, 'Word': 'sheet'}]
SERECTHISSHEEREO [{'Pos': 1, 'Word': 'erect'}, {'Pos': 9, 'Word': 'sheer'}]
SERECTHISSHEEPEO [{'Pos': 1, 'Word': 'erect'}, {'Pos': 9, 'Word': 'sheep'}]
SERECTHISSHEAVEO [{'Pos': 1, 'Word': 'erect'}, {'Pos': 10, 'Word': 'heave'}]
SERECTHISSHENCEO [{'Pos': 1, 'Word': 'erect'}, {'Pos': 10, 'Word': 'hence'}]
SERECTHISSHELLEO [{'Pos': 1, 'Word': 'erect'}, {'Pos': 9, 'Word': 'shell'}]
SERECTHISSHELFEO [{'Pos': 1, 'Word': 'erect'}, {'Pos': 9, 'Word': 'shelf'}]
SERECTHISSHEDGEO [{'Pos': 1, 'Word': 'erect'}, {'Pos': 10, 'Word': 'hedge'}]
SELECTHISSHEETEO [{'Pos': 1, 'Word': 'elect'}, {'Pos': 9, 'Word': 'sheet'}]
SELECTHISSHEEREO [{'Pos': 1, 'Word': 'elect'}, {'Pos': 9, 'Word': 'sheer'}]
SELECTHISSHEEPEO [{'Pos': 1, 'Word': 'elect'}, {'Pos': 9, 'Word': 'sheep'}]
SELECTHISSHEAVEO [{'Pos': 1, 'Word': 'elect'}, {'Pos': 10, 'Word': 'heave'}]
SELECTHISSHENCEO [{'Pos': 1, 'Word': 'elect'}, {'Pos': 10, 'Word': 'hence'}]
SELECTHISSHELLEO [{'Pos': 1, 'Word': 'elect'}, {'Pos': 9, 'Word': 'shell'}]
SELECTHISSHELFEO [{'Pos': 1, 'Word': 'elect'}, {'Pos': 9, 'Word': 'shelf'}]
SELECTHISSHEDGEO [{'Pos': 1, 'Word': 'elect'}, {'Pos': 10, 'Word': 'hedge'}]
SEXACTHISSHAREAO [{'Pos': 1, 'Word': 'exact'}, {'Pos': 9, 'Word': 'share'}]
SEXACTHISSHARPAO [{'Pos': 1, 'Word': 'exact'}, {'Pos': 9, 'Word': 'sharp'}]
SEXACTHISSHALTAO [{'Pos': 1, 'Word': 'exact'}, {'Pos': 9, 'Word': 'shalt'}]
SEXACTHISSHALLAO [{'Pos': 1, 'Word': 'exact'}, {'Pos': 9, 'Word': 'shall'}]
SEXACTHISSHADEAO [{'Pos': 1, 'Word': 'exact'}, {'Pos': 9, 'Word': 'shade'}]
SEXACTHISSHADYAO [{'Pos': 1, 'Word': 'exact'}, {'Pos': 9, 'Word': 'shady'}]
SEXACTHISSHAMEAO [{'Pos': 1, 'Word': 'exact'}, {'Pos': 9, 'Word': 'shame'}]
SEXACTHISSHAFTAO [{'Pos': 1, 'Word': 'exact'}, {'Pos': 9, 'Word': 'shaft'}]
SEXACTHISSHAPEAO [{'Pos': 1, 'Word': 'exact'}, {'Pos': 9, 'Word': 'shape'}]
SEXACTHISSHAWLAO [{'Pos': 1, 'Word': 'exact'}, {'Pos': 9, 'Word': 'shawl'}]
SEXACTHISSHAKEAO [{'Pos': 1, 'Word': 'exact'}, {'Pos': 9, 'Word': 'shake'}]
CTION HI
WHICH HI
THESE HI
SEATSTHISSHTASTE [{'Pos': 0, 'Word': 'seats'}, {'Pos': 11, 'Word': 'taste'}]
SEXESTHISSHEETEE [{'Pos': 0, 'Word': 'sexes'}, {'Pos': 9, 'Word': 'sheet'}]
SEXESTHISSHEEREE [{'Pos': 0, 'Word': 'sexes'}, {'Pos': 9, 'Word': 'sheer'}]
SEXESTHISSHEEPEE [{'Pos': 0, 'Word': 'sexes'}, {'Pos': 9, 'Word': 'sheep'}]
SEXESTHISSHEAVEE [{'Pos': 0, 'Word': 'sexes'}, {'Pos': 10, 'Word': 'heave'}]
SEXESTHISSHENCEE [{'Pos': 0, 'Word': 'sexes'}, {'Pos': 10, 'Word': 'hence'}]
SEXESTHISSHELLEE [{'Pos': 0, 'Word': 'sexes'}, {'Pos': 9, 'Word': 'shell'}]
SEXESTHISSHELFEE [{'Pos': 0, 'Word': 'sexes'}, {'Pos': 9, 'Word': 'shelf'}]
SEXESTHISSHEDGEE [{'Pos': 0, 'Word': 'sexes'}, {'Pos': 10, 'Word': 'hedge'}]
SEXISTHISSHINEIE [{'Pos': 1, 'Word': 'exist'}, {'Pos': 9, 'Word': 'shine'}]
SEXISTHISSHIRTIE [{'Pos': 1, 'Word': 'exist'}, {'Pos': 9, 'Word': 'shirt'}]
SEXISTHISSHIFTIE [{'Pos': 1, 'Word': 'exist'}, {'Pos': 9, 'Word': 'shift'}]
SEXISTHISSHIPSIE [{'Pos': 1, 'Word': 'exist'}, {'Pos': 9, 'Word': 'ships'}]
AFTER HI
STAREAHISSHRUGRR [{'Pos': 0, 'Word': 'stare'}, {'Pos': 9, 'Word': 'shrug'}]
STOREAHISSHRUGRR [{'Pos': 0, 'Word': 'store'}, {'Pos': 9, 'Word': 'shrug'}]
EOFTH HI
ABOUT HI
ERTHE HI
IONAL HI
FIRST HI
WOULD HI
List complete

Interesting QT, looks like you’re onto something.