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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