the ususal nlp libraries like Open NLP, LingPipe, NLTK, Gate, UIMA. All of these provide parsers and word stemmers (i.e. they don't give you back the root of a word, but its stem). Some also provide lemmatizers.
I'm not aware of a tool which returns the root of a word, but, as I said, there are stemmers and lemmatizers. For lemmatization, try Tree Tagger or Morpha. Morphophonemic analysis is a term not specific enough to get you what you want.
Once you know more specifically what you need, you could search the archives of the Corpora List or post a question there.
NTLK is an interesting toolkit which allows building NLP-based applications. This can be used for practical applications which require for example POS tagging, or which implement simple classifiers or entity extractors.
I'm unsure of what a "language understander" application would encompass, however, but this sounds like something which may be beyond what can [easily] be based upon NLTK. Reading the question completely, and its reference to morphophonics, seems to confirm that NLTK would probably not serve the OP's purpose very well; to my knowledge NTLK doesn't offer modules that deal with text at this level. You may want to check this for yourself however, as NLTK is a broad and active project and may have seen recent additions in this area.
>> client.interpret phrase: 'Set up a meeting with Bob tomorrow \
night at 7 PM to discuss the TPS reports'
=>
{:entities=>
{
:daterange=>[{:start=>"2012-11-15", :end=>"2012-11-16"}],
:title=>["meeting to discuss the tps reports"],
:timerange=>[{:start=>"12:00:00AM", :end=>"12:00:00AM"}],
:contacts=>[{:name=>"bob"}]
},
:action=>:CALENDAR_CREATE_EVENT,
:category=>:CALENDAR
}
For an example of the power of it, take this query as an example of what can be extracted:
>> client.interpret phrase: 'Set up a meeting with Bob tomorrow \
night at 7 PM to discuss the TPS reports'
=>
{:entities=>
{
:daterange=>[{:start=>"2012-11-15", :end=>"2012-11-16"}],
:title=>["meeting to discuss the tps reports"],
:timerange=>[{:start=>"12:00:00AM", :end=>"12:00:00AM"}],
:contacts=>[{:name=>"bob"}]
},
:action=>:CALENDAR_CREATE_EVENT,
:category=>:CALENDAR
}
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评论（4）
我建议你看一下以下内容：
我不知道有什么工具可以返回单词的词根，但是，正如我所说，有词干分析器和词形还原器。对于词形还原，请尝试 Tree Tagger 或 Morpha。形态音素分析这个术语不够具体，无法满足您的需求。
一旦您更具体地知道您需要什么，您可以搜索语料库列表的档案或发布那里有一个问题。
I suggest you take a look at the following:
I'm not aware of a tool which returns the root of a word, but, as I said, there are stemmers and lemmatizers. For lemmatization, try Tree Tagger or Morpha. Morphophonemic analysis is a term not specific enough to get you what you want.
Once you know more specifically what you need, you could search the archives of the Corpora List or post a question there.
NTLK 是一个有趣的工具包，可以构建基于 NLP 的应用程序。这可用于需要 POS 标记或实现简单分类器或实体提取器的实际应用。
然而，我不确定“语言理解器”应用程序将包含什么内容，但这听起来可能超出了[轻松]基于 NLTK 的范围。
完整地阅读这个问题及其对形态学的引用，似乎证实了 NLTK 可能不能很好地满足 OP 的目的；据我所知，NTLK 不提供处理此级别文本的模块。不过，您可能需要亲自检查一下，因为 NLTK 是一个广泛且活跃的项目，并且可能已经看到了该领域最近的新增内容。
NTLK is an interesting toolkit which allows building NLP-based applications. This can be used for practical applications which require for example POS tagging, or which implement simple classifiers or entity extractors.
I'm unsure of what a "language understander" application would encompass, however, but this sounds like something which may be beyond what can [easily] be based upon NLTK.
Reading the question completely, and its reference to morphophonics, seems to confirm that NLTK would probably not serve the OP's purpose very well; to my knowledge NTLK doesn't offer modules that deal with text at this level. You may want to check this for yourself however, as NLTK is a broad and active project and may have seen recent additions in this area.
我想附上 MontyLingua python 包的链接，可以在这里找到。我认为它使用与 nltk 不同的解析器。
http://www.fslog.com/2008 /09/20/montylingua3-gpled-fork-of-montylingua/
你可以google一下和nltk的比较。
I want to chime in with a link to the MontyLingua python package, which can be found here. I think it uses a different parser than the nltk.
http://www.fslog.com/2008/09/20/montylingua3-gpled-fork-of-montylingua/
you can google a comparison with nltk.
Maluuba 刚刚发布了其自然语言处理器的 API。它位于 http://developer.maluuba.com。
Maluuba 为其编写了三个库：
Python 库： https://github.com/maluuba/napi- python
Ruby 库：https://github.com/maluuba/napi-ruby
Java 库：https://github.com/maluuba/napi-java
有关示例它的力量，以这个查询为例，说明可以提取什么：
Maluuba has just released an API to their Natural Language Processor. It's available at http://developer.maluuba.com.
There are three libraries written for it by Maluuba:
Python Library: https://github.com/maluuba/napi-python
Ruby Library: https://github.com/maluuba/napi-ruby
Java Library: https://github.com/maluuba/napi-java
For an example of the power of it, take this query as an example of what can be extracted: