linguistics

问题 I am using NSLinguisticTagger for word stemming. I am able to get a stem words of words in a sentence, but not able to get a stem word for a single word. Following is the code I am using, NSString *stmnt = @"i waited"; NSLinguisticTaggerOptions options = NSLinguisticTaggerOmitWhitespace | NSLinguisticTaggerOmitPunctuation | NSLinguisticTaggerJoinNames; NSLinguisticTagger *tagger = [[NSLinguisticTagger alloc] initWithTagSchemes:@[NSLinguisticTagSchemeLemma] options:options]; tagger.string =

问题 I am using NSLinguisticTagger for word stemming. I am able to get a stem words of words in a sentence, but not able to get a stem word for a single word. Following is the code I am using, NSString *stmnt = @"i waited"; NSLinguisticTaggerOptions options = NSLinguisticTaggerOmitWhitespace | NSLinguisticTaggerOmitPunctuation | NSLinguisticTaggerJoinNames; NSLinguisticTagger *tagger = [[NSLinguisticTagger alloc] initWithTagSchemes:@[NSLinguisticTagSchemeLemma] options:options]; tagger.string =

问题 I was wondering if anyone was familiar with any attempts at algorithmic sentence negation. For example, given a sentence like "This book is good" provide any number of alternative sentences meaning the opposite like "This book is not good" or even "This book is bad". Obviously, accomplishing this with a high degree of accuracy would probably be beyond the scope of current NLP, but I'm sure there has been some work on the subject. If anybody knows of any work, care to point me to some papers?

问题 I was wondering if anyone was familiar with any attempts at algorithmic sentence negation. For example, given a sentence like "This book is good" provide any number of alternative sentences meaning the opposite like "This book is not good" or even "This book is bad". Obviously, accomplishing this with a high degree of accuracy would probably be beyond the scope of current NLP, but I'm sure there has been some work on the subject. If anybody knows of any work, care to point me to some papers?

问题 Does anyone have a suggestion for where to find archives or collections of everyday English text for use in a small corpus? I have been using Gutenberg Project books for a working prototype, and would like to incorporate more contemporary language. A recent answer here pointed indirectly to a great archive of usenet movie reviews, which hadn't occurred to me, and is very good. For this particular program technical usenet archives or programming mailing lists would tilt the results and be hard

问题 Does nltk or any other NLP tool allow to construct probability trees based on input sentences thus storing the language model of the input text in a dictionary tree, the following example gives the rough idea, but I need the same functionality such that a word Wt does not just probabilistically modelled on past input words(history) Wt-n but also on lookahead words like Wt+m. Also the lookback and lookahead word count should also be 2 or more i.e. bigrams or more. Are there any other libraries

问题 Q1.I am trying to get tense of a complete sentence,just don't know how to do it using nlp. Any help appreciated. Q2 .What all information can be extracted from a sentence using nlp? Currently I can, I get : 1.Voice of sentence 2.subject object verb 3.POS tags. Any more info can be extracted please let me know. 回答1: The Penn treebank defines VBD and VBN as the past tense and the past participle of a verb, respectively. In many sentences, simply getting the POS tags and checking for the

问题 Q1.I am trying to get tense of a complete sentence,just don't know how to do it using nlp. Any help appreciated. Q2 .What all information can be extracted from a sentence using nlp? Currently I can, I get : 1.Voice of sentence 2.subject object verb 3.POS tags. Any more info can be extracted please let me know. 回答1: The Penn treebank defines VBD and VBN as the past tense and the past participle of a verb, respectively. In many sentences, simply getting the POS tags and checking for the

问题 I have a .NET application where, given a noun, I want it to correctly prefix that word with "a" or "an". How would I do that? Before you think the answer is to simply check if the first letter is a vowel, consider phrases like: an honest mistake a used car 回答1: Download Wikipedia Unzip it and write a quick filter program that spits out only article text (the download is generally in XML format, along with non-article metadata too). Find all instances of a(n).... and make an index on the

问题 I am experimenting with word sense disambiguation using wordnet for my project. As a part of the project, I would like to convert a derived adjective or an adverb form to it's root noun form. For example beautiful ==> beauty wonderful ==> wonder How can I achieve this? Is there any other dict other than wordnet that provides this kind of transformation? It would be an added bonus for me if I can map the exact sense of the adjective word to its noun form with exact sense. Is that possible?