data:image/png;base64,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

index1word guessed?

i1true

false

Takes a text string as input, and reports a new text string containing all but the first character of the input.

pt:_ sem o primeiro caractere resulti2

Takes a text string as input, divides it into words treating one or more spaces as a word separator (only spaces count; punctuation is part of the word) and reports a text string containing all but the first word, with one space between words and no spaces at the beginning or end. (Note: consider using SENTENCE->LIST and processing the resulting list instead of doing recursion on sentences in text string form. List operations are faster.)

pt:_ sem a primeira palavra

Takes a text string as input, and reports a new text string containing all but the last letter of the input.

pt:_ sem o último caractere resulti1

Takes a text string as input, divides it into words treating one or more spaces as a word separator (only spaces count; punctuation is part of the word) and reports a text string containing all but the last word, with one space between words and no spaces at the beginning or end. (Note: consider using SENTENCE->LIST and processing the resulting list instead of doing recursion on sentences in text string form. List operations are faster.)

pt:_ sem a última palavra 1 1 11 1

pt:a primeira palavra de _

Takes a text string as input, and reports the last character in the string.

pt:o último caractere de _

pt:a última palavra de _ 1 1

Takes a text string as input, and reports TRUE if the string has no characters in it of any kind, otherwise false.

pt:a palavra _ está vazia

Takes a text string as input, and reports TRUE if the input contains no characters other than spaces (therefore, no words when the string is considered as a sentence), otherwise FALSE.

pt:a frase _ está vazia

de:füge Wörter zusammen _ ca:uneix les paraules _ es:unir las palabras _ fr:fusionne les mots _ pt:uma frase com as palavras _ 121

de:Liste $arrowRight Satz _ ca:llista $arrowRight frase _ es:lista $arrowRight frase _ fr:liste $arrowRight phrase _ pt:uma frase com as palavras em _

de:Satz $arrowRight Liste _ ca:frase $arrowRight llista _ es:frase $arrowRight lista _ fr:phrase $arrowRight liste _ pt:uma lista com as palavras da frase _

report a list in which each item is one letter from the input word

de:Wort $arrowRight Liste _ ca:paraula $arrowRight llista _ es:palabra $arrowRight lista _ fr:mot $arrowRight liste _ pt:uma lista com os caracteres da palavra _

join all the items of the input list into a single word, and report it

de:Liste $arrowRight Wort _ ca:llista $arrowRight paraula _ es:lista $arrowRight palabra _ fr:liste $arrowRight mot _ pt:uma palavra com os caracteres em _

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