Minor documentation fixes (#2864)

* Minor documentation fixes

* Fix unicode characters in doctest

nltk/test/wordnet.doctest

@@ -6,6 +6,7 @@ WordNet Interface
 =================
 
 WordNet is just another NLTK corpus reader, and can be imported like this:
+
     >>> from nltk.corpus import wordnet
 
 For more compact code, we recommend:
@@ -53,11 +54,10 @@ WordNet, using ISO-639 language codes.
     >>> wn.synsets(b'\xe7\x8a\xac'.decode('utf-8'), lang='jpn')
     [Synset('dog.n.01'), Synset('spy.n.01')]
 
-    wn.synset('spy.n.01').lemma_names('jpn')
-    ['\u3044\u306c', '\u307e\u308f\u3057\u8005', '\u30b9\u30d1\u30a4', '\u56de\u3057\u8005',
-    '\u56de\u8005', '\u5bc6\u5075', '\u5de5\u4f5c\u54e1', '\u5efb\u3057\u8005',
-    '\u5efb\u8005', '\u63a2', '\u63a2\u308a', '\u72ac', '\u79d8\u5bc6\u635c\u67fb\u54e1',
-    '\u8adc\u5831\u54e1', '\u8adc\u8005', '\u9593\u8005', '\u9593\u8adc', '\u96a0\u5bc6']
+    >>> wn.synset('spy.n.01').lemma_names('jpn')
+    ['いぬ', 'スパイ', '回者', '回し者', '密偵', '工作員',
+    '廻者', '廻し者', '探', '探り', '犬', '秘密捜査員',
+    'まわし者', '諜報員', '諜者', '間者', '間諜', '隠密']
 
     >>> wn.synset('dog.n.01').lemma_names('ita')
     ['cane', 'Canis_familiaris']
@@ -68,8 +68,8 @@ WordNet, using ISO-639 language codes.
     [Lemma('dog.n.01.hund'), Lemma('dog.n.01.k\xf8ter'),
     Lemma('dog.n.01.vovhund'), Lemma('dog.n.01.vovse')]
 
-    sorted(wn.synset('dog.n.01').lemmas('por'))
-	[Lemma('dog.n.01.cachorra'), Lemma('dog.n.01.cachorro'), Lemma('dog.n.01.cadela'), Lemma('dog.n.01.c\xe3o')]
+    >>> sorted(wn.synset('dog.n.01').lemmas('por'))
+    [Lemma('dog.n.01.cachorra'), Lemma('dog.n.01.cachorro'), Lemma('dog.n.01.cadela'), Lemma('dog.n.01.c\xe3o')]
 
     >>> dog_lemma = wn.lemma(b'dog.n.01.c\xc3\xa3o'.decode('utf-8'), lang='por')
     >>> dog_lemma
@@ -450,6 +450,7 @@ as a base form for a POS for which that word is not defined:
     >>> wn.morphy('book', wn.NOUN)
     'book'
     >>> wn.morphy('book', wn.ADJ)
+    >>>
 
 Bug 160: wup_similarity breaks when the two synsets have no common hypernym
 
@@ -460,6 +461,7 @@ Bug 160: wup_similarity breaks when the two synsets have no common hypernym
 
     Issue #2278: wup_similarity not commutative when comparing a noun and a verb.
     Patch #2650 resolved this error. As a result, the output of the following use of wup_similarity no longer returns None.
+
     >>> t = wn.synsets('titan')[1]
     >>> s = wn.synsets('say', wn.VERB)[0]
     >>> t.wup_similarity(s)
@@ -598,6 +600,7 @@ Bug https://github.com/nltk/nltk/issues/1641: Non-English lemmas containing capi
     [Lemma('united_kingdom.n.01.Londres'), Lemma('london.n.01.Londres'), Lemma('london.n.02.Londres')]
 
 Patch-1 https://github.com/nltk/nltk/pull/2065  Adding 3 functions (relations) to WordNet class
+
     >>> wn.synsets("computer_science")[0].in_topic_domains()[2]
     Synset('access_time.n.01')
     >>> wn.synsets("France")[0].in_region_domains()[18]