Apa semua kemungkinan tag pos NLTK?

Bagaimana cara menemukan daftar dengan semua kemungkinan tag pos yang digunakan oleh Natural Language Toolkit (nltk)?

Buku ini memiliki catatan cara menemukan bantuan pada set tag, misalnya:

nltk.help.upenn_tagset()

Yang lain mungkin serupa. (Catatan: Mungkin Anda pertama kali harus mengunduh tagsetsdari bagian Models helper untuk ini)

Untuk menghemat waktu beberapa orang, berikut adalah daftar yang saya ekstrak dari sebuah korpus kecil. Saya tidak tahu apakah sudah selesai, tetapi seharusnya memiliki sebagian besar (jika tidak semua) definisi bantuan dari upenn_tagset ...

CC : konjungsi, koordinasi

& 'n and both but either et for less minus neither nor or plus so
therefore times v. versus vs. whether yet

CD : angka, kardinal

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 ...

DT : penentu

all an another any both del each either every half la many much nary
neither no some such that the them these this those

EX : ada di sana

there

DALAM : preposisi atau konjungsi, bawahan

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 ...

JJ : kata sifat atau angka, urut

third ill-mannered pre-war regrettable oiled calamitous first separable
ectoplasmic battery-powered participatory fourth still-to-be-named
multilingual multi-disciplinary ...

JJR : kata sifat, komparatif

bleaker braver breezier briefer brighter brisker broader bumper busier
calmer cheaper choosier cleaner clearer closer colder commoner costlier
cozier creamier crunchier cuter ...

JJS : kata sifat, superlatif

calmest cheapest choicest classiest cleanest clearest closest commonest
corniest costliest crassest creepiest crudest cutest darkest deadliest
dearest deepest densest dinkiest ...

LS : daftar item marker

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

MD : tambahan modal

can cannot could couldn't dare may might must need ought shall should
shouldn't will would

NN : kata benda, umum, tunggal atau massa

common-carrier cabbage knuckle-duster Casino afghan shed thermostat
investment slide humour falloff slick wind hyena override subhumanity
machinist ...

NNP : kata benda, tepat, tunggal

Motown Venneboerger Czestochwa Ranzer Conchita Trumplane Christos
Oceanside Escobar Kreisler Sawyer Cougar Yvette Ervin ODI Darryl CTCA
Shannon A.K.C. Meltex Liverpool ...

NNS : kata benda, umum, jamak

undergraduates scotches bric-a-brac products bodyguards facets coasts
divestitures storehouses designs clubs fragrances averages
subjectivists apprehensions muses factory-jobs ...

PDT : pra-penentu

all both half many quite such sure this

POS : penanda genitif

' 's

PRP : kata ganti, pribadi

hers herself him himself hisself it itself me myself one oneself ours
ourselves ownself self she thee theirs them themselves they thou thy us

PRP $: kata ganti, posesif

her his mine my our ours their thy your

RB : kata keterangan

occasionally unabatingly maddeningly adventurously professedly
stirringly prominently technologically magisterially predominately
swiftly fiscally pitilessly ...

RBR : kata keterangan, komparatif

further gloomier grander graver greater grimmer harder harsher
healthier heavier higher however larger later leaner lengthier less-
perfectly lesser lonelier longer louder lower more ...

RBS : kata keterangan, superlatif

best biggest bluntest earliest farthest first furthest hardest
heartiest highest largest least less most nearest second tightest worst

RP : partikel

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

TO : "to" sebagai preposisi atau penanda infinitif

to

UH : kata seru

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 ...

VB : kata kerja, bentuk dasar

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 ...

VBD : kata kerja, past tense

dipped pleaded swiped regummed soaked tidied convened halted registered
cushioned exacted snubbed strode aimed adopted belied figgered
speculated wore appreciated contemplated ...

VBG : kata kerja, present participle atau gerund

telegraphing stirring focusing angering judging stalling lactating
hankerin' alleging veering capping approaching traveling besieging
encrypting interrupting erasing wincing ...

VBN : kata kerja, past participle

multihulled dilapidated aerosolized chaired languished panelized used
experimented flourished imitated reunifed factored condensed sheared
unsettled primed dubbed desired ...

VBP : kata kerja, present tense, bukan ke 3 orang tunggal

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 ...

VBZ : kata kerja, present tense, 3rd person singular

bases reconstructs marks mixes displeases seals carps weaves snatches
slumps stretches authorizes smolders pictures emerges stockpiles
seduces fizzes uses bolsters slaps speaks pleads ...

WDT : WH-determiner

that what whatever which whichever

WP : Kata ganti WH

that what whatever whatsoever which who whom whosoever

WRB : Wh-adverbia

how however whence whenever where whereby whereever wherein whereof why

Set tag tergantung pada corpus yang digunakan untuk melatih tagger. Tagger default nltk.pos_tag()menggunakan Penn Treebank Tag Set .

Di NLTK 2, Anda dapat memeriksa tagger mana yang merupakan tagger default sebagai berikut:

import nltk
nltk.tag._POS_TAGGER
>>> 'taggers/maxent_treebank_pos_tagger/english.pickle'

Itu berarti bahwa itu adalah tagger Entropy Maksimum yang dilatih di Treebank corpus.

nltk.tag._POS_TAGGERtidak ada lagi di NLTK 3 tetapi dokumentasi menyatakan bahwa tag -off-the-shelf masih menggunakan tagset Penn Treebank.

Di bawah ini dapat bermanfaat untuk mengakses dict yang dikunci dengan singkatan:

>>> 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', ...

Referensi tersedia di situs resmi

Salin dan tempel dari sana:

• CC | Konjungsi koordinasi |
• CD | Nomor telepon |
• DT | Penentu |
• EX | Eksistensial di sana |
• FW | Kata asing |
• DALAM | Preposisi atau konjungsi bawahan |
• JJ | Kata sifat |
• JJR | Adjektiva, komparatif |
• JJS | Adjektiva, superlatif |
• LS | Daftar penanda item |
• MD | Modal |
• NN | Kata benda, tunggal atau massal |
• NNS | Jamak, jamak |
• NNP | Kata benda yang tepat, singular |
• NNPS | Kata benda yang tepat, jamak |
• PDT | Predeterminer |
• POS | Akhir yang posesif |
• PRP | Kata ganti pribadi |
• PRP $ | Kata ganti posesif |
• BPR | Adverbia |
• RBR | Adverbia, komparatif |
• RBS | Adverbia, superlatif |
• RP | Partikel |
• SYM | Simbol |
• UNTUK | untuk |
• UH | Interjeksi |
• VB | Kata kerja, bentuk dasar |
• VBD | Kata kerja, past tense |
• VBG | Kata kerja, gerund, atau partisip sekarang |
• VBN | Kata kerja, past participle |
• VBP | Verb, non-3rd person singular present |
• VBZ | Kata kerja, orang ketiga hadir tunggal |
• WDT | Penentu-| |
• WP | Kata ganti |
• WP $ | Posesif wh-kata ganti |
• WRB | Kata keterangan |

Anda dapat mengunduh daftar di sini: ftp://ftp.cis.upenn.edu/pub/treebank/doc/tagguide.ps.gz . Ini termasuk bagian-bagian pembicaraan yang membingungkan, huruf besar, dan konvensi lainnya. Juga, wikipedia memiliki bagian menarik yang mirip dengan ini. Bagian: Tag sebagian ucapan yang digunakan.

['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']

Berdasarkan metode Doug Shore tetapi membuatnya lebih ramah copy-paste

Jalankan saja kata demi kata ini.

import nltk
nltk.download('tagsets')
nltk.help.upenn_tagset()

nltk.tag._POS_TAGGERtidak akan bekerja Ini akan memberikan AttributeError: module 'nltk.tag' tidak memiliki atribut '_POS_TAGGER' . Ini tidak tersedia di NLTK 3 lagi.