Python NLTK所有可能的pos标签是什么？
如何查找包含自然语言工具包（nltk）使用的所有可能pos标记的列表？有一个关于如何查找标记集帮助的说明，例如：Python NLTK所有可能的pos标签是什么？,python,nltk,Python,Nltk,如何查找包含自然语言工具包（nltk）使用的所有可能pos标记的列表？有一个关于如何查找标记集帮助的说明，例如： nltk.help.upenn_tagset() 其他人可能也类似。（注意：可能您首先必须从下载助手的模型部分下载标记集）标记集取决于用于训练标记者的语料库。 nltk.pos_tag（）的默认标记器使用 在NLTK 2中，您可以检查哪个标记器是默认标记器，如下所示： import nltk nltk.tag._POS_TAGGER >>> 'taggers/ma
nltk.help.upenn_tagset()
其他人可能也类似。（注意：可能您首先必须从下载助手的模型部分下载标记集）标记集取决于用于训练标记者的语料库。
nltk.pos_tag（）import nltk
nltk.tag._POS_TAGGER
>>> 'taggers/maxent_treebank_pos_tagger/english.pickle'
nltk.tag.\u POS\u TAGGER>>> from nltk.data import load
>>> tagdict = load('help/tagsets/upenn_tagset.pickle')
>>> tagdict['NN'][0]
'noun, common, singular or mass'
>>> tagdict.keys()
['PRP$', 'VBG', 'VBD', '``', 'VBN', ',', "''", 'VBP', 'WDT', ...
为了节省一些人的时间，下面是我从一个小语料库中提取的一个列表。我不知道它是否完整，但它应该包含来自upenn_标记集的大部分（如果不是全部）帮助定义 CC：连词，协调词
& 'n and both but either et for less minus neither nor or plus so
therefore times v. versus vs. whether yet
astride among uppon whether out inside pro despite on by throughout
below within for towards near behind atop around if like until below
next into if beside ...
mid-1890 nine-thirty forty-two one-tenth ten million 0.5 one forty-
seven 1987 twenty '79 zero two 78-degrees eighty-four IX '60s .025
fifteen 271,124 dozen quintillion DM2,000 ...
all an another any both del each either every half la many much nary
neither no some such that the them these this those
all both half many quite such sure this
that what whatever which whichever
there
& 'n and both but either et for less minus neither nor or plus so
therefore times v. versus vs. whether yet
astride among uppon whether out inside pro despite on by throughout
below within for towards near behind atop around if like until below
next into if beside ...
third ill-mannered pre-war regrettable oiled calamitous first separable
ectoplasmic battery-powered participatory fourth still-to-be-named
multilingual multi-disciplinary ...
bleaker braver breezier briefer brighter brisker broader bumper busier
calmer cheaper choosier cleaner clearer closer colder commoner costlier
cozier creamier crunchier cuter ...
further gloomier grander graver greater grimmer harder harsher
healthier heavier higher however larger later leaner lengthier less-
perfectly lesser lonelier longer louder lower more ...
calmest cheapest choicest classiest cleanest clearest closest commonest
corniest costliest crassest creepiest crudest cutest darkest deadliest
dearest deepest densest dinkiest ...
best biggest bluntest earliest farthest first furthest hardest
heartiest highest largest least less most nearest second tightest worst
A A. B B. C C. D E F First G H I J K One SP-44001 SP-44002 SP-44005
SP-44007 Second Third Three Two * a b c d first five four one six three
two
can cannot could couldn't dare may might must need ought shall should
shouldn't will would
common-carrier cabbage knuckle-duster Casino afghan shed thermostat
investment slide humour falloff slick wind hyena override subhumanity
machinist ...
Motown Venneboerger Czestochwa Ranzer Conchita Trumplane Christos
Oceanside Escobar Kreisler Sawyer Cougar Yvette Ervin ODI Darryl CTCA
Shannon A.K.C. Meltex Liverpool ...
undergraduates scotches bric-a-brac products bodyguards facets coasts
divestitures storehouses designs clubs fragrances averages
subjectivists apprehensions muses factory-jobs ...
all an another any both del each either every half la many much nary
neither no some such that the them these this those
all both half many quite such sure this
that what whatever which whichever
' 's
to
hers herself him himself hisself it itself me myself one oneself ours
ourselves ownself self she thee theirs them themselves they thou thy us
her his mine my our ours their thy your
occasionally unabatingly maddeningly adventurously professedly
stirringly prominently technologically magisterially predominately
swiftly fiscally pitilessly ...
bleaker braver breezier briefer brighter brisker broader bumper busier
calmer cheaper choosier cleaner clearer closer colder commoner costlier
cozier creamier crunchier cuter ...
further gloomier grander graver greater grimmer harder harsher
healthier heavier higher however larger later leaner lengthier less-
perfectly lesser lonelier longer louder lower more ...
calmest cheapest choicest classiest cleanest clearest closest commonest
corniest costliest crassest creepiest crudest cutest darkest deadliest
dearest deepest densest dinkiest ...
best biggest bluntest earliest farthest first furthest hardest
heartiest highest largest least less most nearest second tightest worst
aboard about across along apart around aside at away back before behind
by crop down ever fast for forth from go high i.e. in into just later
low more off on open out over per pie raising start teeth that through
under unto up up-pp upon whole with you
' 's
to
Goodbye Goody Gosh Wow Jeepers Jee-sus Hubba Hey Kee-reist Oops amen
huh howdy uh dammit whammo shucks heck anyways whodunnit honey golly
man baby diddle hush sonuvabitch ...
ask assemble assess assign assume atone attention avoid bake balkanize
bank begin behold believe bend benefit bevel beware bless boil bomb
boost brace break bring broil brush build ...
dipped pleaded swiped regummed soaked tidied convened halted registered
cushioned exacted snubbed strode aimed adopted belied figgered
speculated wore appreciated contemplated ...
telegraphing stirring focusing angering judging stalling lactating
hankerin' alleging veering capping approaching traveling besieging
encrypting interrupting erasing wincing ...
multihulled dilapidated aerosolized chaired languished panelized used
experimented flourished imitated reunifed factored condensed sheared
unsettled primed dubbed desired ...
predominate wrap resort sue twist spill cure lengthen brush terminate
appear tend stray glisten obtain comprise detest tease attract
emphasize mold postpone sever return wag ...
bases reconstructs marks mixes displeases seals carps weaves snatches
slumps stretches authorizes smolders pictures emerges stockpiles
seduces fizzes uses bolsters slaps speaks pleads ...
predominate wrap resort sue twist spill cure lengthen brush terminate
appear tend stray glisten obtain comprise detest tease attract
emphasize mold postpone sever return wag ...
bases reconstructs marks mixes displeases seals carps weaves snatches
slumps stretches authorizes smolders pictures emerges stockpiles
seduces fizzes uses bolsters slaps speaks pleads ...
all an another any both del each either every half la many much nary
neither no some such that the them these this those
all both half many quite such sure this
that what whatever which whichever
that what whatever whatsoever which who whom whosoever
how however whence whenever where whereby whereever wherein whereof why
参考资料可在 从那里复制和粘贴：
- CC |协调连接|
- CD |基数|
- DT |限定符|
- 这里是存在的|
- FW |外来词|
- 介词或从属连词|
- JJ |形容词|
- 形容词，比较级|
- 形容词，最高级|
- LS |列表项标记|
- MD |模态|
- NN |名词，单数或质量|
- NNS |名词，复数|
- NNP |专有名词，单数|
- NNPS |专有名词，复数|
- PDT |预先决定者|
- POS |所有格结尾|
- PRP |人称代词|
- PRP$|所有格代词|
- RB |副词|
- 比较副词|
- RBS |副词，最高级|
- RP |粒子|
- 符号|
- 至|至|
- 呃|叹词|
- VB |动词，基本形式|
- VBD |动词，过去时|
- VBG |动词、动名词或现在分词|
- 动词，过去分词|
- VBP |动词，非第三人称单数出现|
- VBZ |动词，第三人称单数出现|
- WDT | Wh限定词|
- WP | Wh代词|
- WP$|所有格wh代词|
- WRB | Wh副词|
import nltk
nltk.download('tagsets')
nltk.help.upenn_tagset()
nltk.tag.\u POS\u TAGGER['LS', 'TO', 'VBN', "''", 'WP', 'UH', 'VBG', 'JJ', 'VBZ', '--', 'VBP', 'NN', 'DT', 'PRP', ':', 'WP$', 'NNPS', 'PRP$', 'WDT', '(', ')', '.', ',', '``', '$', 'RB', 'RBR', 'RBS', 'VBD', 'IN', 'FW', 'RP', 'JJR', 'JJS', 'PDT', 'MD', 'VB', 'WRB', 'NNP', 'EX', 'NNS', 'SYM', 'CC', 'CD', 'POS']
基于Doug Shore的方法，但要使其更易于复制粘贴谢谢你，在我看来，这是一个比公认的答案更有用的答案。这是一个不完整的答案。首先，
nltk.tag.\u POS\u TAGGERRB副词nltk.help.upenn_标记集（'RB'）