data:image/png;base64,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data:image/png;base64,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

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 0

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 01 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 _ 0

pt:a última palavra de _ index01 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 0

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 index10

Like JOIN, takes any number of words (text strings) and reports a sentence with its inputs concatenated, but inserts a blank space between the inputs. Consider using SENTENCE (Lists palette) instead.

de:füge Wörter zusammen _ ca:uneix les paraules _ es:unir las palabras _ fr:fusionne les mots _ pt:uma frase com as palavras _ 1121

Takes a sentence in list form and reports the sentence as a text string.

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

Takes a sentence in text string form and reports the sentence as a list of its words.

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 _

SENTENCE is the main constructor for sentences, represented as lists of words. It takes zero or more inputs, each of which can be either a list or a text string. If a list, the input is assumed to be a list of words. If a text string, it is converted to a list of words using SENTENCE→LIST. Then all the lists of words are appended to form a new list of words. If the inputs are lists of lists rather than lists of words, SENTENCE, like APPEND, does only one level of flattening, reporting a list of all the items of all the input lists.

pt:lança o erro _

Takes a (possibly deep) list as input, and reports a human-readable text form of the list (namely, Lisp notation).

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