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 ca:_ sense la primera lletra

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 ca:_ sense la primera paraula

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 ca:_ sense la darrera lletra

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 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 ca:_ sense la darrera paraula

All but last of empty sentence.

pt:a primeira palavra de _ ca:primera paraula de _

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

pt:o último caractere de _ ca:primera lletra de _ 0

pt:a última palavra de _ ca:darrera paraula de _

Last of empty sentence.

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 ca:paraula buida? _ 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 ca:frase buida? _

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.

ca:frase _

pt:lança o erro _

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

ca:notació textual de _ (

)

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 _ ca:primera lletra de _

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_, _, _, _, _, _, _20t