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This chapter continues to present programming concepts by example, in the context of a linguistic processing task.

We will wait until later before exploring each Python construct systematically.

Unfortunately, for many languages, substantial corpora are not yet available.

Often there is insufficient government or industrial support for developing language resources, and individual efforts are piecemeal and hard to discover or re-use.

The graph in fig-inaugural used "word offset" as one of the axes; this is the numerical index of the word in the corpus, counting from the first word of the first address.

However, the corpus is actually a collection of 55 texts, one for each presidential address.

We examined some small text collections in 1., such as the speeches known as the US Presidential Inaugural Addresses.

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(See 7 for suggestions on how to locate language resources.) We have seen a variety of corpus structures so far; these are summarized in 1.3.The corpus contains over 10,000 posts, anonymized by replacing usernames with generic names of the form "User NNN", and manually edited to remove any other identifying information.The corpus is organized into 15 files, where each file contains several hundred posts collected on a given date, for an age-specific chatroom (teens, 20s, 30s, 40s, plus a generic adults chatroom).: Common Structures for Text Corpora: The simplest kind of corpus is a collection of isolated texts with no particular organization; some corpora are structured into categories like genre (Brown Corpus); some categorizations overlap, such as topic categories (Reuters Corpus); other corpora represent language use over time (Inaugural Address Corpus).

NLTK's corpus readers support efficient access to a variety of corpora, and can be used to work with new corpora.

For convenience, the corpus methods accept a single fileid or a list of fileids.



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