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Java Stanford NLP : 음성 레이블의 일부?
here 데모 된 Stanford NLP 는 다음과 같은 출력을 제공합니다.
Colorless/JJ green/JJ ideas/NNS sleep/VBP furiously/RB ./.
품사 태그의 의미는 무엇입니까? 공식 목록을 찾을 수 없습니다. 스탠포드 자체 시스템입니까, 아니면 범용 태그를 사용하고 있습니까? ( JJ예를 들어 무엇입니까?)
또한 문장을 반복하고 명사를 찾을 때 태그가 있는지 확인하는 것과 같은 일을 끝내게됩니다 .contains('N'). 이것은 꽤 약한 느낌입니다. 말의 특정 부분을 프로그래밍 방식으로 검색하는 더 좋은 방법이 있습니까?
펜 트리 뱅크 프로젝트 . 상기 봐 품사 태깅 PS.
JJ는 형용사입니다. NNS는 명사, 복수입니다. VBP는 동사 시제입니다. RB는 부사입니다.
그것은 영어입니다. 중국인은 Penn Chinese Treebank입니다. 그리고 독일에게는 네 그라 코퍼스입니다.
- CC 코디네이 팅 합동
- CD 추기경 번호
- DT 결정기
- EX 존재
- FW 외국어
- IN 전치사 또는 대체 조합
- JJ 형용사
- JJR 형용사, 비교
- JJS 형용사, 최상급
- LS 목록 항목 마커
- MD 모달
- NN 명사, 단수 또는 질량
- NNS 명사, 복수
- NNP 고유 명사, 단수
- NNPS 적절한 명사, 복수
- PDT 사전 결정자
- POS 소유 엔딩
- PRP 개인 대명사
- PRP $ 소유 대명사
- RB 부사
- RBR 부사, 비교
- 최상급 RBS 부사
- RP 입자
- 기호
- 에
- UH 감청
- VB 동사, 기본형
- 과거 시제 VBD 동사
- VBG 동사, 제럴드 또는 현재 분사
- VBN 동사, 과거 분사
- VBP 동사, 3 인이 아닌 단수 선물
- VBZ 동사, 3 인칭 단수 선물
- WDT Whdeterminer
- WP 워프 론운
- WP $ 소유 whpronoun
- WRB Whadverb
Explanation of each tag from the documentation :
CC: conjunction, coordinating
& 'n and both but either et for less minus neither nor or plus so
therefore times v. versus vs. whether yet
CD: numeral, cardinal
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
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
there
FW: foreign word
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
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
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
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
calmest cheapest choicest classiest cleanest clearest closest commonest
corniest costliest crassest creepiest crudest cutest darkest deadliest
dearest deepest densest dinkiest ...
LS: list 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: modal auxiliary
can cannot could couldn't dare may might must need ought shall should
shouldn't will would
NN: noun, common, singular or mass
common-carrier cabbage knuckle-duster Casino afghan shed thermostat
investment slide humour falloff slick wind hyena override subhumanity
machinist ...
NNS: noun, common, plural
undergraduates scotches bric-a-brac products bodyguards facets coasts
divestitures storehouses designs clubs fragrances averages
subjectivists apprehensions muses factory-jobs ...
NNP: noun, proper, singular
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
Americans Americas Amharas Amityvilles Amusements Anarcho-Syndicalists
Andalusians Andes Andruses Angels Animals Anthony Antilles Antiques
Apache Apaches Apocrypha ...
PDT: pre-determiner
all both half many quite such sure this
POS: genitive marker
' 's
PRP: pronoun, personal
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
her his mine my our ours their thy your
RB: adverb
occasionally unabatingly maddeningly adventurously professedly
stirringly prominently technologically magisterially predominately
swiftly fiscally pitilessly ...
RBR: adverb, comparative
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
best biggest bluntest earliest farthest first furthest hardest
heartiest highest largest least less most nearest second tightest worst
RP: particle
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
SYM: symbol
% & ' '' ''. ) ). * + ,. < = > @ A[fj] U.S U.S.S.R * ** ***
TO: "to" as preposition or infinitive marker
to
UH: interjection
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: verb, base form
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: verb, past tense
dipped pleaded swiped regummed soaked tidied convened halted registered
cushioned exacted snubbed strode aimed adopted belied figgered
speculated wore appreciated contemplated ...
VBG: verb, present participle or gerund
telegraphing stirring focusing angering judging stalling lactating
hankerin' alleging veering capping approaching traveling besieging
encrypting interrupting erasing wincing ...
VBN: verb, past participle
multihulled dilapidated aerosolized chaired languished panelized used
experimented flourished imitated reunifed factored condensed sheared
unsettled primed dubbed desired ...
VBP: verb, present tense, not 3rd person singular
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: verb, 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: WH-pronoun
that what whatever whatsoever which who whom whosoever
WP$: WH-pronoun, possessive
whose
WRB: Wh-adverb
how however whence whenever where whereby whereever wherein whereof why
위에 허용 된 답변에 다음 정보가 없습니다.
9 개의 문장 부호 태그도 정의되어 있습니다 (일부 참조에 나열되지 않음, 여기 참조 ). 이것들은:
- #
- $
- ''(모든 형태의 마감 인용에 사용)
- ((모든 형태의 여는 괄호에 사용)
- ) (모든 형태의 닫는 괄호에 사용됨)
- ,
- . (모든 문장 끝 구두점에 사용됨)
- : (콜론, 세미콜론 및 타원에 사용)
- ``(모든 형태의 오프닝 견적에 사용)
다음은 Penn Treebank에 대한 전체 태그 목록입니다 (완료를 위해 게시 됨).
http://www.surdeanu.info/mihai/teaching/ista555-fall13/readings/PennTreebankConstituents.html
또한 절 및 구문 수준에 대한 태그도 포함합니다.
조항 수준
- S
- SBAR
- SBARQ
- SINV
- SQ
문구 수준
- ADJP
- ADVP
- CONJP
- FRAG
- INTJ
- LST
- NAC
- NP
- NX
- PP
- PRN
- PRT
- QP
- RRC
- UCP
- VP
- WHADJP
- WHAVP
- WHNP
- WHPP
- X
(링크 설명)
코드를 작성하려는 경우를 대비하여 ...
/**
* Represents the English parts-of-speech, encoded using the
* de facto <a href="http://www.cis.upenn.edu/~treebank/">Penn Treebank
* Project</a> standard.
*
* @see <a href="ftp://ftp.cis.upenn.edu/pub/treebank/doc/tagguide.ps.gz">Penn Treebank Specification</a>
*/
public enum PartOfSpeech {
ADJECTIVE( "JJ" ),
ADJECTIVE_COMPARATIVE( ADJECTIVE + "R" ),
ADJECTIVE_SUPERLATIVE( ADJECTIVE + "S" ),
/* This category includes most words that end in -ly as well as degree
* words like quite, too and very, posthead modi ers like enough and
* indeed (as in good enough, very well indeed), and negative markers like
* not, n't and never.
*/
ADVERB( "RB" ),
/* Adverbs with the comparative ending -er but without a strictly comparative
* meaning, like <i>later</i> in <i>We can always come by later</i>, should
* simply be tagged as RB.
*/
ADVERB_COMPARATIVE( ADVERB + "R" ),
ADVERB_SUPERLATIVE( ADVERB + "S" ),
/* This category includes how, where, why, etc.
*/
ADVERB_WH( "W" + ADVERB ),
/* This category includes and, but, nor, or, yet (as in Y et it's cheap,
* cheap yet good), as well as the mathematical operators plus, minus, less,
* times (in the sense of "multiplied by") and over (in the sense of "divided
* by"), when they are spelled out. <i>For</i> in the sense of "because" is
* a coordinating conjunction (CC) rather than a subordinating conjunction.
*/
CONJUNCTION_COORDINATING( "CC" ),
CONJUNCTION_SUBORDINATING( "IN" ),
CARDINAL_NUMBER( "CD" ),
DETERMINER( "DT" ),
/* This category includes which, as well as that when it is used as a
* relative pronoun.
*/
DETERMINER_WH( "W" + DETERMINER ),
EXISTENTIAL_THERE( "EX" ),
FOREIGN_WORD( "FW" ),
LIST_ITEM_MARKER( "LS" ),
NOUN( "NN" ),
NOUN_PLURAL( NOUN + "S" ),
NOUN_PROPER_SINGULAR( NOUN + "P" ),
NOUN_PROPER_PLURAL( NOUN + "PS" ),
PREDETERMINER( "PDT" ),
POSSESSIVE_ENDING( "POS" ),
PRONOUN_PERSONAL( "PRP" ),
PRONOUN_POSSESSIVE( "PRP$" ),
/* This category includes the wh-word whose.
*/
PRONOUN_POSSESSIVE_WH( "WP$" ),
/* This category includes what, who and whom.
*/
PRONOUN_WH( "WP" ),
PARTICLE( "RP" ),
/* This tag should be used for mathematical, scientific and technical symbols
* or expressions that aren't English words. It should not used for any and
* all technical expressions. For instance, the names of chemicals, units of
* measurements (including abbreviations thereof) and the like should be
* tagged as nouns.
*/
SYMBOL( "SYM" ),
TO( "TO" ),
/* This category includes my (as in M y, what a gorgeous day), oh, please,
* see (as in See, it's like this), uh, well and yes, among others.
*/
INTERJECTION( "UH" ),
VERB( "VB" ),
VERB_PAST_TENSE( VERB + "D" ),
VERB_PARTICIPLE_PRESENT( VERB + "G" ),
VERB_PARTICIPLE_PAST( VERB + "N" ),
VERB_SINGULAR_PRESENT_NONTHIRD_PERSON( VERB + "P" ),
VERB_SINGULAR_PRESENT_THIRD_PERSON( VERB + "Z" ),
/* This category includes all verbs that don't take an -s ending in the
* third person singular present: can, could, (dare), may, might, must,
* ought, shall, should, will, would.
*/
VERB_MODAL( "MD" ),
/* Stanford.
*/
SENTENCE_TERMINATOR( "." );
private final String tag;
private PartOfSpeech( String tag ) {
this.tag = tag;
}
/**
* Returns the encoding for this part-of-speech.
*
* @return A string representing a Penn Treebank encoding for an English
* part-of-speech.
*/
public String toString() {
return getTag();
}
protected String getTag() {
return this.tag;
}
public static PartOfSpeech get( String value ) {
for( PartOfSpeech v : values() ) {
if( value.equals( v.getTag() ) ) {
return v;
}
}
throw new IllegalArgumentException( "Unknown part of speech: '" + value + "'." );
}
}
여기에 전체 목록을 제공하고 참조 링크도 제공합니다
1. CC Coordinating conjunction
2. CD Cardinal number
3. DT Determiner
4. EX Existential there
5. FW Foreign word
6. IN Preposition or subordinating conjunction
7. JJ Adjective
8. JJR Adjective, comparative
9. JJS Adjective, superlative
10. LS List item marker
11. MD Modal
12. NN Noun, singular or mass
13. NNS Noun, plural
14. NNP Proper noun, singular
15. NNPS Proper noun, plural
16. PDT Predeterminer
17. POS Possessive ending
18. PRP Personal pronoun
19. PRP$ Possessive pronoun
20. RB Adverb
21. RBR Adverb, comparative
22. RBS Adverb, superlative
23. RP Particle
24. SYM Symbol
25. TO to
26. UH Interjection
27. VB Verb, base form
28. VBD Verb, past tense
29. VBG Verb, gerund or present participle
30. VBN Verb, past participle
31. VBP Verb, non-3rd person singular present
32. VBZ Verb, 3rd person singular present
33. WDT Wh-determiner
34. WP Wh-pronoun
35. WP$ Possessive wh-pronoun
36. WRB Wh-adverb
품사 태그의 전체 목록은 여기에서 확인할 수 있습니다 .
특정 POS (예 : 명사) 태그 단어 / 청크를 찾는 두 번째 질문과 관련하여 수행 할 수있는 샘플 코드는 다음과 같습니다.
public static void main(String[] args) {
Properties properties = new Properties();
properties.put("annotators", "tokenize, ssplit, pos, lemma, ner, parse");
StanfordCoreNLP pipeline = new StanfordCoreNLP(properties);
String input = "Colorless green ideas sleep furiously.";
Annotation annotation = pipeline.process(input);
List<CoreMap> sentences = annotation.get(CoreAnnotations.SentencesAnnotation.class);
List<String> output = new ArrayList<>();
String regex = "([{pos:/NN|NNS|NNP/}])"; //Noun
for (CoreMap sentence : sentences) {
List<CoreLabel> tokens = sentence.get(CoreAnnotations.TokensAnnotation.class);
TokenSequencePattern pattern = TokenSequencePattern.compile(regex);
TokenSequenceMatcher matcher = pattern.getMatcher(tokens);
while (matcher.find()) {
output.add(matcher.group());
}
}
System.out.println("Input: "+input);
System.out.println("Output: "+output);
}
출력은 다음과 같습니다.
Input: Colorless green ideas sleep furiously.
Output: [ideas]
그들은 갈색 코퍼스 태그 인 것 같습니다 .
다른 언어에 대한 Stanford CoreNLP 태그 : 프랑스어, 스페인어, 독일어 ...
기본 모델 인 영어 파서를 사용하는 것이 보입니다. 다른 언어 (프랑스어, 스페인어, 독일어 ...)에 파서를 사용할 수 있으며 토크 나이저와 음성 태그의 일부는 언어마다 다릅니다. 그렇게하려면 언어에 대한 특정 모델 (예 : Maven과 같은 빌더 사용)을 다운로드 한 다음 사용하려는 모델을 설정해야합니다. 여기에 더 많은 정보가 있습니다.
다음은 다양한 언어에 대한 태그 목록입니다.
- 스페인어 용 Stanford CoreNLP POS 태그
- 독일어 스탠포드 CoreNLP POS 술래는 용도 스투 트가 르트 - 튀빙겐 태그 세트 (STTS를)
- 프랑스어 용 Stanford CoreNLP POS 태거는 다음 태그를 사용합니다.
프랑스어 태그 :
프랑스어 음성 태그의 일부
A (adjective)
Adv (adverb)
CC (coordinating conjunction)
Cl (weak clitic pronoun)
CS (subordinating conjunction)
D (determiner)
ET (foreign word)
I (interjection)
NC (common noun)
NP (proper noun)
P (preposition)
PREF (prefix)
PRO (strong pronoun)
V (verb)
PONCT (punctuation mark)
프랑스어에 대한 문구 카테고리 태그 :
AP (adjectival phrases)
AdP (adverbial phrases)
COORD (coordinated phrases)
NP (noun phrases)
PP (prepositional phrases)
VN (verbal nucleus)
VPinf (infinitive clauses)
VPpart (nonfinite clauses)
SENT (sentences)
Sint, Srel, Ssub (finite clauses)
프랑스어 구문 기능 :
SUJ (subject)
OBJ (direct object)
ATS (predicative complement of a subject)
ATO (predicative complement of a direct object)
MOD (modifier or adjunct)
A-OBJ (indirect complement introduced by à)
DE-OBJ (indirect complement introduced by de)
P-OBJ (indirect complement introduced by another preposition)
참고 URL : https://stackoverflow.com/questions/1833252/java-stanford-nlp-part-of-speech-labels
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