Java スタンフォード NLP:品詞ラベル?
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11-09-2019 - |
質問
スタンフォード NLP のデモ ここ, 、次のような出力が得られます。
Colorless/JJ green/JJ ideas/NNS sleep/VBP furiously/RB ./.
品詞タグは何を意味しますか?公式のリストが見つかりません。それはスタンフォード大学独自のシステムですか、それともユニバーサルタグを使用していますか?(とは JJ
, 、 例えば?)
また、文章を反復処理して、たとえば名詞を探しているときに、タグが正しいかどうかを確認するなどのことを行うことになります。 .contains('N')
. 。これはかなり弱い気がします。特定の品詞をプログラムで検索するより良い方法はあるでしょうか?
解決
ペン・ツリーバンク・プロジェクト. 。見てください 品詞タグ付け ps。
JJは形容詞です。NNSは名詞、複数形です。VBP は動詞現在形です。RBは副詞です。
それは英語用です。中国人の場合は、ペン・チャイニーズ・ツリーバンクです。そしてドイツ語の場合は NEGRA コーパスです。
- CC 等位結合
- CD 基数
- DT 決定器
- EXそこに存在する
- FW外来語
- IN 前置詞または従属接続詞
- JJ 形容詞
- JJR 形容詞、比較級
- JJS 形容詞、最上級
- LS リスト項目マーカー
- MDモーダル
- NN 名詞、単数または集団
- NNS 名詞、複数
- NNP 固有名詞、単数形
- NNPS 固有名詞、複数形
- PDT 事前決定子
- POS 所有エンディング
- PRP 人称代名詞
- PRP$ 所有代名詞
- RB副詞
- RBR 副詞、比較級
- RBS 副詞、最上級
- RP粒子
- SYMシンボル
- へ へ
- UH 介入
- VB 動詞、基本形
- VBD 動詞、過去形
- VBG 動詞、動名詞、または現在分詞
- VBN 動詞、過去分詞
- VBP 動詞、非三人称単数現在
- VBZ 動詞、三人称単数現在
- WDT 検出器
- WP Wh代名詞
- WP$ 所有権代名詞
- WRB ワド動詞
他のヒント
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
上記の受け入れられた回答には、次の情報が欠落しています。
また、9 個の句読点タグが定義されています (一部の参考文献にはリストされていません。参照) ここ)。これらは:
- #
- $
- '' (あらゆる形式の終了引用符に使用されます)
- ( (すべての形式の開き括弧に使用されます)
- ) (すべての形式の閉じ括弧に使用されます)
- ,
- . 。(文末のすべての句読点に使用されます)
- :(コロン、セミコロン、楕円に使用)
- `` (あらゆる形式の開始引用符に使用されます)
ここの(completnessのためにここに掲載)のペンツリーバンクのタグのより完全なリストです
http://www.surdeanu.info/mihai/teaching/ista555-fall13 /readings/PennTreebankConstituents.htmlする また、句と句レベルのタグが含まれます。 (リンクの説明)の句レベル
- S
- SBAR
- SBARQ
- SINV
- SQ
フレーズレベル
- ADJP
- ADVP
- CONJP
- FRAG
- INTJ
- LST
- NAC
- NP
- NX
- PP
- PRN
- PRT
- QP
- RRC
- UCP
- VP
- WHADJP
- WHAVP
- WHNP
- WHPP
- X
念のためにあなたはそれをコーディングしたいた...
/**
* 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 + "'." );
}
}
私はここに全体のリストを提供し、また、参照リンクを与えている。
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
あなたはスピーチタグここに。
特定のPOS(例えば、名詞)タグ付けされた単語/チャンクを見つけることのあなたの2番目の質問については、ここにあなたが続くことができるサンプルコードです。
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);
}
出力されます:
Input: Colorless green ideas sleep furiously.
Output: [ideas]
これはブラウンコーパスタグであるように見える。
他の言語の Stanford CoreNLP タグ :フランス語、スペイン語、ドイツ語...
デフォルトのモデルである英語用のパーサーを使用しているようですね。他の言語 (フランス語、スペイン語、ドイツ語など) のパーサーを使用することもできますが、トークナイザーと品詞タグ付けの両方が言語ごとに異なることに注意してください。これを行う場合は、その言語の特定のモデルをダウンロードし (たとえば、Maven などのビルダーを使用して)、使用するモデルを設定する必要があります。ここ それについては詳しい情報があります。
以下は、さまざまな言語のタグのリストです。
- スペイン語用の Stanford CoreNLP POS タグ
- Stanford CoreNLP ドイツ語用 POS タガー を使用します シュトゥットガルト - テュービンゲン タグ セット (STTS)
- フランス語の Stanford CoreNLP POS タガーは次のタグを使用します。
フランス語のタグ:
フランス語の品詞タグ
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)
フランス語のフレーズカテゴリタグ:
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)
フランス語の構文関数:
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)