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 strreturn str.slice(1);

All but first of empty word.

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

All but first of empty sentence.

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 strreturn str.slice(0,-1);

All but last of empty word.

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

arrreturn new List(arr.asArray().slice(0,-1));

All but last of empty sentence.

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 _

Last of empty sentence.

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 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

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 _ firstbffirst1

1bf

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).

(

)

Helper function for word/sentence library. Reports its first input, unless that input is empty, in which case it gives its second input as an error message.

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

pt:a primeira palavra de _

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