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).

(

)

false

-1

blank