CoreNLP POS
Last updated
Last updated
CoreNLP POS-tagging is done using CoreNLP Server
using official pre-trained model invoked from fromnltk.parse.corenlp.CoreNLPParser
Quoted from https://nlp.stanford.edu/software/pos-tagger-faq.html
What is the tag set used by the Stanford Tagger?
You can train models for the Stanford POS Tagger with any tag set. For the models we distribute, the tag set depends on the language, reflecting the underlying treebanks that models have been built from. That is, the tag set was wholly or mainly decided by the treebank producers not us). Here are relevant links:
English: the Penn Treebank site. There is an online copy of its documentation; in particular, see TAGGUID1.PDF (POS tagging guide). There are also other simpler listings such as the AMALGAM project page.
UPenn Treebank Docs https://catalog.ldc.upenn.edu/docs/LDC99T42/
python -c "import nltk; nltk.help.upenn_tagset()"
Tag | Description |
---|---|
$
dollar e.g. $
, -$
, --$
, A$
, C$
, HK$
, M$
, NZ$
, S$
, U.S.$
, US$
''
closing quotation mark e.g. '
, ''
(
opening parenthesis e.g. (
, [
, {
,
comma e.g. ,
--
dash e.g. --
.
sentence terminator e.g. .
, !
, ?
:
colon or ellipsis e.g. :
, ;
, ...
``
opening quotation mark e.g. `
, ``
CC
conjunction, coordinating e.g. &
, 'n
, and
, both
, but
, either
, et
, for
, less
, minus
, neither
, nor
, or
, plus
, so
, therefore
, times
, v.
, versus
, vs.
, whether
, yet
CD
numeral, cardinal e.g. 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
determiner e.g. 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
existential there e.g. there
FW
foreign word e.g. gemeinschaft
, hund
, ich
, jeux
, habeas
, Haementeria
, Herr
, K'ang-si
, vous
, lutihaw
, alai
, je
, jour
, objets
, salutaris
, fille
, quibusdam
, pas
, trop
, Monte
, terram
, fiche
, oui
, corporis
, ...
IN
preposition or conjunction, subordinating e.g. 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
adjective or numeral, ordinal e.g. third
, ill-mannered
, pre-war
, regrettable
, oiled
, calamitous
, first
, separable
, ectoplasmic
, battery-powered
, participatory
, fourth
, still-to-be-named
, multilingual
, multi-disciplinary
, ...
JJR
adjective, comparative e.g. bleaker
, braver
, breezier
, briefer
, brighter
, brisker
, broader
, bumper
, busier
, calmer
, cheaper
, choosier
, cleaner
, clearer
, closer
, colder
, commoner
, costlier
, cozier
, creamier
, crunchier
, cuter
, ...
JJS
adjective, superlative e.g. calmest
, cheapest
, choicest
, classiest
, cleanest
, clearest
, closest
, commonest
, corniest
, costliest
, crassest
, creepiest
, crudest
, cutest
, darkest
, deadliest
, dearest
, deepest
, densest
, dinkiest
, ...
LS
list item marker e.g. 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
modal auxiliary e.g. can
, cannot
, could
, couldn't
, dare
, may
, might
, must
, need
, ought
, shall
, should
, shouldn't
, will
, would
NN
noun, common, singular or mass e.g. common-carrier
, cabbage
, knuckle-duster
, Casino
, afghan
, shed
, thermostat
, investment
, slide
, humour
, falloff
, slick
, wind
, hyena
, override
, subhumanity
, machinist
, ...
NNP
noun, proper, singular e.g. Motown
, Venneboerger
, Czestochwa
, Ranzer
, Conchita
, Trumplane
, Christos
, Oceanside
, Escobar
, Kreisler
, Sawyer
, Cougar
, Yvette
, Ervin
, ODI
, Darryl
, CTCA
, Shannon
, A.K.C.
, Meltex
, Liverpool
, ...
NNPS
noun, proper, plural e.g. Americans
, Americas
, Amharas
, Amityvilles
, Amusements
, Anarcho-Syndicalists
, Andalusians
, Andes
, Andruses
, Angels
, Animals
, Anthony
, Antilles
, Antiques
, Apache
, Apaches
, Apocrypha
, ...
NNS
noun, common, plural e.g. undergraduates
, scotches
, bric-a-brac
, products
, bodyguards
, facets
, coasts
, divestitures
, storehouses
, designs
, clubs
, fragrances
, averages
, subjectivists
, apprehensions
, muses
, factory-jobs
, ...
PDT
pre-determiner e.g. all
, both
, half
, many
, quite
, such
, sure
, this
POS
genitive marker e.g. '
, 's
PRP
pronoun, personal e.g. 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$
pronoun, possessive e.g. her
, his
, mine
, my
, our
, ours
, their
, thy
, your
RB
adverb e.g. occasionally
, unabatingly
, maddeningly
, adventurously
, professedly
, stirringly
, prominently
, technologically
, magisterially
, predominately
, swiftly
, fiscally
, pitilessly
, ...
RBR
adverb, comparative e.g. 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
adverb, superlative e.g. best
, biggest
, bluntest
, earliest
, farthest
, first
, furthest
, hardest
, heartiest
, highest
, largest
, least
, less
, most
, nearest
, second
, tightest
, worst
RBS
adverb, superlative e.g. best
, biggest
, bluntest
, earliest
, farthest
, first
, furthest
, hardest
, heartiest
, highest
, largest
, least
, less
, most
, nearest
, second
, tightest
, worst
RBS
particle e.g. 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