By Steven Bird, Ewan Klein

This e-book bargains a hugely obtainable creation to usual language processing, the sphere that helps quite a few language applied sciences, from predictive textual content and e mail filtering to computerized summarization and translation. With it, you'll tips on how to write Python courses that paintings with huge collections of unstructured textual content. You'll entry richly annotated datasets utilizing a entire diversity of linguistic info constructions, and you'll comprehend the most algorithms for studying the content material and constitution of written communication.

Packed with examples and workouts, Natural Language Processing with Python can help you:

Extract info from unstructured textual content, both to wager the subject or determine "named entities"
Analyze linguistic constitution in textual content, together with parsing and semantic analysis
Access well known linguistic databases, together with WordNet and treebanks
Integrate thoughts drawn from fields as varied as linguistics and synthetic intelligence
This publication can assist you achieve functional abilities in normal language processing utilizing the Python programming language and the common Language Toolkit (NLTK) open resource library. If you're drawn to constructing internet purposes, studying multilingual information resources, or documenting endangered languages -- or if you're easily curious to have a programmer's point of view on how human language works -- you'll locate Natural Language Processing with Python either attention-grabbing and immensely priceless.

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Extra info for Natural Language Processing with Python

Example text

Word = 'cat' >>> if len(word) < 5: ... print 'word length is less than 5' ... word length is less than 5 >>> When we use the Python interpreter we have to add an extra blank line it to detect that the nested block is complete. in order for If we change the conditional test to len(word) >= 5, to check that the length of word is greater than or equal to 5, then the test will no longer be true. This time, the body of the if statement will not be executed, and no message is shown to the user: >>> if len(word) >= 5: ...

Serve: help with food or drink; hold an office; put ball into play b. dish: plate; course of a meal; communications device In a sentence containing the phrase: he served the dish, you can detect that both serve and dish are being used with their food meanings. It’s unlikely that the topic of discussion shifted from sports to crockery in the space of three words. 5 Automatic Natural Language Understanding | 27 laid out beside the court. In other words, we automatically disambiguate words using context, exploiting the simple fact that nearby words have closely related meanings.

Limitations of NLP Despite the research-led advances in tasks such as RTE, natural language systems that have been deployed for real-world applications still cannot perform common-sense reasoning or draw on world knowledge in a general and robust manner. We can wait for these difficult artificial intelligence problems to be solved, but in the meantime it is necessary to live with some severe limitations on the reasoning and knowledge capabilities of natural language systems. Accordingly, right from the beginning, an important goal of NLP research has been to make progress on the difficult task of building technologies that “understand language,” using superficial yet powerful techniques 32 | Chapter 1: Language Processing and Python instead of unrestricted knowledge and reasoning capabilities.

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