data:image/png;base64,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data:image/png;base64,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55

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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