diff --git a/chatter.cabal b/chatter.cabal
--- a/chatter.cabal
+++ b/chatter.cabal
@@ -1,5 +1,5 @@
 name:                chatter
-version:             0.5.0.0
+version:             0.5.0.1
 synopsis:            A library of simple NLP algorithms.
 description:         chatter is a collection of simple Natural Language
                      Processing algorithms.
diff --git a/src/NLP/Chunk.hs b/src/NLP/Chunk.hs
--- a/src/NLP/Chunk.hs
+++ b/src/NLP/Chunk.hs
@@ -1,4 +1,31 @@
 {-# LANGUAGE OverloadedStrings #-}
+{-|
+Module      : NLP.Chunk
+Description : Phrase Chunking facilities.
+Copyright   : Rogan Creswick, 2014
+Maintainer  : creswick@gmail.com
+Stability   : experimental
+
+NLP.Chunk aims to make phrasal chunking trivially easy -- it is the
+corolary to NLP.POS.
+
+The simplest way to try out chunking with Chatter is to open a repl
+after installing chatter and try this:
+
+>> import NLP.POS
+>> import NLP.Chunk
+>> tgr <- defaultTagger
+>> chk <- defaultChunker
+>> chunkText tgr chk "Monads are monoids in the category of endofunctors."
+> "[NP Monads/NNS are/VBP monoids/NNS] [PP in/IN] [NP the/DT category/NN] [PP of/IN] [NP endofunctors/NNS] ./."
+
+Note that it isn't perfect--phrase chunking is tricky, and the
+'defaultTagger' and 'defaultChunker' aren't trained on the largest
+training set (they use Conll 2000).  You can easily train more taggers
+and chunkers using the APIs exposed here if you have the training data
+to do so.
+
+-}
 module NLP.Chunk
 where
 
diff --git a/src/NLP/Chunk/AvgPerceptronChunker.hs b/src/NLP/Chunk/AvgPerceptronChunker.hs
--- a/src/NLP/Chunk/AvgPerceptronChunker.hs
+++ b/src/NLP/Chunk/AvgPerceptronChunker.hs
@@ -1,4 +1,5 @@
 {-# LANGUAGE OverloadedStrings #-}
+{--}
 -- | Avegeraged Perceptron Chunker
 --
 module NLP.Chunk.AvgPerceptronChunker
diff --git a/src/NLP/Corpora/Email.hs b/src/NLP/Corpora/Email.hs
--- a/src/NLP/Corpora/Email.hs
+++ b/src/NLP/Corpora/Email.hs
@@ -6,8 +6,9 @@
 import Data.List (isSuffixOf)
 import Data.Text (Text)
 import qualified Data.Text.Encoding as TE
+import qualified Data.Text.Lazy as LT
 
-import Data.MBox
+import Data.MBox (body, Message, parseMBox)
 
 import System.Directory (getDirectoryContents)
 import System.FilePath ((</>))
@@ -21,12 +22,12 @@
 plugArchiveText :: IO [Text]
 plugArchiveText = do
   archive <- fullPlugArchive
-  return $ map body archive
+  return $ map (LT.toStrict . body) archive
 
 plugArchiveTokens :: IO [[Text]]
 plugArchiveTokens = do
   archive <- fullPlugArchive
-  return $ map (tokenize . body) archive
+  return $ map (tokenize . LT.toStrict . body) archive
 
 fullPlugArchive :: IO [Message]
 fullPlugArchive = do
@@ -35,7 +36,7 @@
   contents <- mapM (\f->readF (plugDataPath </> f)) archiveFiles
   return $ concatMap parseMBox contents
 
-readF :: FilePath -> IO Text
+readF :: FilePath -> IO LT.Text
 readF file = do
   bs <- BS.readFile file
-  return $ TE.decodeLatin1 bs
+  return $ LT.fromStrict $ TE.decodeLatin1 bs
diff --git a/src/NLP/POS.hs b/src/NLP/POS.hs
--- a/src/NLP/POS.hs
+++ b/src/NLP/POS.hs
@@ -1,24 +1,31 @@
 {-# LANGUAGE OverloadedStrings #-}
--- | This module aims to make tagging text with parts of speech
--- trivially easy.
---
--- If you're new to 'chatter' and POS-tagging, then I
--- suggest you simply try:
---
--- >>> tagger <- defaultTagger
--- >>> tagStr tagger "This is a sample sentence."
--- "This/dt is/bez a/at sample/nn sentence/nn ./."
---
--- Note that we used 'tagStr', instead of 'tag', or 'tagText'.  Many
--- people don't (yet!) use "Data.Text" by default, so there is a
--- wrapper around 'tag' that packs and unpacks the 'String'.  This is
--- innefficient, but it's just to get you started, and 'tagStr' can be
--- very handy when you're debugging a tagger in ghci (or cabal repl).
---
--- 'tag' exposes more details of the tokenization and tagging, since
--- it returns a list of `TaggedSentence`s, but it doesn't print
--- results as nicely.
---
+{-|
+Module      : NLP.POS
+Description : Part-of-Speech tagging facilities.
+Copyright   : Rogan Creswick, 2014
+Maintainer  : creswick@gmail.com
+Stability   : experimental
+
+This module aims to make tagging text with parts of speech
+trivially easy.
+
+If you're new to 'chatter' and POS-tagging, then I
+suggest you simply try:
+
+>>> tagger <- defaultTagger
+>>> tagStr tagger "This is a sample sentence."
+"This/dt is/bez a/at sample/nn sentence/nn ./."
+
+Note that we used 'tagStr', instead of 'tag', or 'tagText'.  Many
+people don't (yet!) use "Data.Text" by default, so there is a
+wrapper around 'tag' that packs and unpacks the 'String'.  This is
+innefficient, but it's just to get you started, and 'tagStr' can be
+very handy when you're debugging a tagger in ghci (or cabal repl).
+
+'tag' exposes more details of the tokenization and tagging, since
+it returns a list of `TaggedSentence`s, but it doesn't print
+results as nicely.
+-}
 module NLP.POS
   ( tag
   , tagStr