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1

2 Table of Contents

3 = etc.

4 1. ( + + ( )) 2. :,,,,,, (MUC 1 ) (subj: person, i-obj: org. ) 1 Message Understanding Conference

5 ( ) UGC 2 ( ) : : 2 User-Generated Content

6 [ 12] BCCWJ[ 09] 5 ( ) ( ) (F ) twitter 3,680 1,

7 ( ) :,,,,,, :,,,,,,,

8 [Momouchi 80] [Hamada 00] [ 07]

9 + 1.[Neubig, Mori, et al. 11] KyTea (Cf., MeCab, JUMAN,...) 2. (F), (Q), (T), (D), (Sf), (St), (Ac), (Af)

10 ( ) 3. [Flannery, Mori, et al.] EDA (Cf. CaboCha, KNP,...) 4. [Yoshino, Mori, et al.] Ac( : - F, : T ) 1

11 [ 12]

12 : BCCWJ 53,899 1,834,784 11, , ,109 9, , ,402 BCCWJ: [ 09] : 242 7,023 1, ,966 3,797 12,426

13 Step1. ( ) : : : -:

14 ,, 1. ( ) ( :, ) ( :, ) 3.

15 ( ) ( ) (, etc.)

16 1. : [ 09] 2. ( )

17 ( ) + (,, ) ( : - v.s. - ) ( ) ( ) ( ) ( ) ) ( )

18 : Cf. [ 09] ) - = - - ( ) (MeCab, JUMAN )

19 (KyTea [Neubig 11]) 2 SVM x i 2 x i 1 x i x i+1 x i+2 x i+3 : t i : Char (type) 1-gram feature: -3/ (K), -2/ (H), -1/ (K), 1/ (K), 2/ (H), 3/ (S) Char (type) 2-gram feature: -3/ (KH), -2/ (HK), -1/ (KK), 1/ (KH), 2/ (HS) Char (type) 3-gram feature: -3/ (KHK), -2/ (HKK), -1/ (KKH), 1/ (KHS)!!

20 1. [Mori 96] ( ) 2. # ( =1362) # ( =1338)

21 Web(Yahoo! ) ( ) (F ) 95.54% ( ) 96.75% ( ) 97.15% 75 80% 20 25%

22 : BCCWJ, UniDic, : 8 : F ( ) = LCS/ = LCS/ LCS : longest common subsequence

23 F-measure Work time [hour] ( : 99% )

24 Step 2. (Named Entity) :,,,,,, (MUC) date person org. BIO2 (Begin, Intermediate, Other) /B-Dat /I-Dat /I-Dat /I-Dat /B-Per /I-Per /O /B-Org /O /O /O /O (HMM, CRF) = {B, I} NE-Type {O} : 80% 90% (1 )

25 ... : (F), (Q), (T), (D), (Sf), (St), (Ac), (Af) F Q T Ac Af F Ac Ac

26 !! 1. BIO2 (1 1 ) /B-F /B-Q /I-Q /O /BT /O /B-Ac /O /B-Af /I-Af /O /B-F /I-F /I-F /I-F /O /B-Ac /O /O /B-Ac /O /O 2. (KyTea -solver 6 ) Cf. CRF

27 ( ) 3. w P(y w) B-F I-F B-Q y I-Q B-T O

28 ( ) 3. w P(y w) B-F I-F B-Q y I-Q B-T O : F-I Q-I

29 (242 ) (5 ) : 1/10 : 2/10 10/10

30 F F-measure Training corpus size ex. = 11, %, 1,038, %)

31 F F-measure Training corpus size ex. 5 (243 ) 250 (12,150 )

32 Step 3. Cf. CaboCha, KNP

33 (EDA) [Flannery 11] (MST) 1. σ( i, d i, w), w i w di 2. (MST) ˆ d = argmax d D n σ( i, d i, w) i=1!!

34 ( ) w i 3 w i 2 w i 1 w i w i+1 w i+2 w i+3 w di 3 w di 2 w di 1 w di w di +1 w di +2 w di +3 F1 w i w di F2 w i w di F3 w i w di F4 w i w di 3 F5 w i w di 3

35 : 2 : 11,700, 145,925 : 9,023, 263,425 :

36 Accuracy Work time [hour] (96.83%)

37 Step 4. [Yoshino, Mori, et al.] 1. Ac(Chef, F Q, T ) 2. - Af (Food), Ac (Chef, F, F ) Ac (Chef, F ) 4

38 [Yoshino, Mori, et al.]!!

39 1. : ,966 3,797 12, : (BCCWJ + etc.) + : 1/10 + 9/10 ( ) : ( + ) + :

40 ( )

41 Step 1. : 95.46% (8 ) : 95.84% Step 2. : 53.42% (5 ) : 67.02% Step 3. : 92.58% (8 ) : 93.02% F-measure F-measure Accuracy Work time [hour] Training corpus size Work time [hour]

42 1. ( ) :, : -,, : F : 42.01% ( ) 28.0%! : 58.27% F (21 ) (67.02% 90%)!!

43 (or ) : = = =... ( ) : - : ( ) ( ) : Mix = {,,...} : : =??g

44

45 1. 2. ( : )

46 PNAT ( 1 3 ) ( )? or?

47

48 References Flannery, D., Miyao, Y., Neubig, G., and Mori, S.: Training Dependency Parsers from Partially Annotated Corpora, in Proceedings of the Fifth International Joint Conference on Natural Language Processing (2011) Hamada, R., Ide, I., Sakai, S., and Tanaka, H.: Structural Analysis of Cooking Preparation Steps in Japanese, in Proceedings of the fifth international workshop on Information retrieval with Asian languages, No. 8 in IRAL 00, pp (2000) Momouchi, Y.: Control Structures for Actions in Procedural Texts and PT-Chart, in Proceedings of the Eighth International Conference on Computational Linguistics, pp (1980)

49 Mori, S. and Nagao, M.: Word Extraction from Corpora and Its Part-of-Speech Estimation Using Distributional Analysis, in Proceedings of the 16th International Conference on Computational Linguistics (1996) Neubig, G., Nakata, Y., and Mori, S.: Pointwise Prediction for Robust, Adaptable Japanese Morphological Analysis, in Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics (2011) Yoshino, K., Mori, S., and Kawahara, T.: Predicate Argument Structure Analysis using Partially Annotated Corpora, in Proceedings of the Sixth International Joint Conference on Natural Language Processing (2013)

50 ,,,, Vol. J90-DII, No. 10, pp (2007),,,, (2009),, Vol. 27, No. 4 (2012),, Vol. 24, No. 5, pp (2009)

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