"beza1e1" <[EMAIL PROTECTED]> wrote in message news:[EMAIL PROTECTED] > I'm writing a parser for english language. This is a simple function to > identify, what kind of sentence we have. Do you think, this class > wrapping is right to represent the result of the function? Further > parsing then checks isinstance(text, Declarative). > > ------------------- > class Sentence(str): pass > class Declarative(Sentence): pass > class Question(Sentence): pass > class Command(Sentence): pass > > def identify_sentence(text): > text = text.strip() > if text[-1] == '.': > return Declarative(text) > elif text[-1] == '!': > return Command(text) > elif text[-1] == '?': > return Question(text) > return text > ------------------- > > At first i just returned the class, then i decided to derive Sentence > from str, so i can insert the text as well. > Andreas -
Are you trying to parse any English sentence, or just a limited form of them? Parsing *any* English sentence (or question or interjection or command) is a ***huge*** undertaking - Google for "natural language" and you will find many efforts (with substantial time and money and manpower resources) working on this problem. Applications range from automated language translation to helpdesk automated analysis. I really suggest you do a bit of research on this topic, just to get an idea of how big this job is. Here's a Wikipedia link: http://en.wikipedia.org/wiki/Natural_language_processing Here are some simple examples, that quickly go beyond subject-predicate-object: I drive a truck. I drive a red truck. I drive a red truck to work. I drive a red truck to the shop to work on it. I drive a red truck to the shop to have some work done on it. I drive a red truck very fast. I drive a red truck through a red light. Then factor in other sentences (past and future tenses, past and future perfect tenses, figurative metaphors) and parsing general English is a major job. The favorite test case of the natural language folks is "Time flies like an arrow," which early auto-translation software converted to "Temporal insects enjoy a pointed projectile." On the other hand, if you plan to limit the type and/or content of the sentences being parsed (such as computer system commands or adventure game inputs, or descriptions of physical objects), then you can scope out a reasonable capability by choosing a vocabulary of known verbs and objects, and avoiding ambiguities (such as "set", as in "I set the set of glasses next to the TV set," or "lead" as in "Lead me to the store that sells lead pencils."). Hope this sheds some light on your task, -- Paul -- http://mail.python.org/mailman/listinfo/python-list
