IPSJ SIG Technical Report Vol.2013-NL-214 No /11/15 1,a) (1) [ ] [ ] [14], [28] [17] 1 Tohoku University, Sendai, Miyagi 980 8
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1 1,a) (1) [ ] [ ] [14], [28] [17] 1 Tohoku University, Sendai, Miyagi , Japan 2 Tokyo Institute of Technology 3 National Institute of Informatics 4 University of Yamanashi 5 Future University Hakodate a) y-matsu@ecei.tohoku.ac.jp (KTC) [12] [11], [36] NAIST (NTC) [8], [43] GDA [32] (KNBC) [44] NTC BCCWJ (BCCWJ-PAS) [33] PropBank [24] FrameNet [26] NomBank [21] OntoNotes [7] NTC [43] KTC NTC KTC NTC c 2013 Information Processing Society of Japan 1
2 KTC NTC [37], [42] [8], [11], [36], [43] KNBC BCCWJ-PAS *1 (i) (ii) (iii) 2 3 *1 KNBC BCCWJ- PAS NTC NAIST (KTC) NAIST (NTC) GDA (GDA) KTC (KNBC) (BCCWJ) NTC (BCCWJ-PAS) FrameNet PropBank NomBank OntoNotes NTC FrameNet PropBank NomBank [9], [17], [30], [31] 1 - [3] BCCWJ-PAS KNBC OntoNotes - KTC NTC KTC (2) a. [ ga ] [ wo ] b. [ wo ] [ ni ] [ ] NTC c 2013 Information Processing Society of Japan 2
3 1 OntoNotes 4 BCCWJ-PAS (, 2011) Yahoo! 6, KTC 4.0 5,000 KNBC 4,186 NTC ,000 BCCWJ-PAS GDA 37,000 FrameNet ,018 PropBank 113,000 NomBank 114,576 OntoNotes 4 209,505 (3) a. [ ga ] [ wo ] b. [ wo ] [ ga ] [27] Agent, Theme, Goal (thematic roles) GDA [40] [18] F 67% 91% *2 *2 PropBank kappa [24] FrameNet 91% [2] NTC 83% KTC 85% [36] NTC BCCWJ [33] [13], [22], [29] 3. NAIST c 2013 Information Processing Society of Japan 3
4 NTC KTC NTC 3.2 NTC 3.1 NTC 5 Web [42] Web *3 NTC NTC + (4) a. [ ga ] [ ni ] [ wo ] b. [ ga ] [ wo ] IPADIC [35] *4 (5) a. *3 NTC 1.5 *4 NTC Web b. c. d. *5 (6) a. [ extra ga ] [ ga ] b. [ extra ga ] [ ga ] [ wo ] (7) a. [ wo ] [ ga ] b. [ϕ exo1 ga ] A B VA B V *6 (8) a. [ no ] [ ga ] b. [ ha ] [ ga ] c. [ ha ] [ ga ] 3.2 [43] NTC 2 30 F *7 *5 *6 *7 2 c 2013 Information Processing Society of Japan 4
5 2 NAIST text corpus (%) (%) F1(%) (808/875) (808/854) (247/256) (247/312) (884/1093) (884/1084) (686/833) (686/827) (435/471) (435/461) (251/362) (251/366) (198/260) (198/257) (55/66) (55/66) (143/194) (143/191) (416/471) (416/445) (330/367) (330/346) (308/320) (308/313) (22/47) (22/33) (86/104) (86/99) (20/27) (20/21) (66/77) (66/78) (112/163) (112/130) (105/145) (105/118) (95/115) (95/106) (10/30) (10/12) (7/18) (7/12) (1/6) (1/1) (6/12) (6/11) (i) (ii) NTC KTC NTC KTC NTC KTC NTC KTC 1 NTC KTC ( 1 ) 1 NTC ( 2 ) Wikipedia BCCWJ NTC ( 3 ) NTC KTC NTC c 2013 Information Processing Society of Japan 5
6 NTC KTC ( 4 ) 1, 000 (2) ( 5 ) NTC KTC 8 (1) (4) BCCWJ 20 *8 (1) (4) *8 Yahoo!Yahoo! 10 OC , OC , OC , OC , OC , OW6X 00007, OW6X 00009, OW6X 00016, OY , OY , OY , OY , PB , PB , PB , PB , PM , PM , PM , PM (9) (a) (b) (c) (a) (10) a. [ ga ] b. [ ga ] c. [ wo ] d. [ wo ] NTC KTC (11) a. [ wo ] c 2013 Information Processing Society of Japan 6
7 3 KTC NTC A B b. [ wo ] [ ga ] c. [ wo ] [ ga ] - (b) (12) a. b. c. d. e. f. g. NTC (1.5 ) KTC a [23] 1 [23] [5] [20] c 2013 Information Processing Society of Japan 7
8 *9 (c) (13a) (13b) b a [19], [34] (13) a. a b b. a b a b b a b NTC KTC NTC [39] (13) a *9 (14) a. NTC NTC 4 IPADIC JUMAN UniDic (1) (2) 6 4 c 2013 Information Processing Society of Japan 8
9 4 IPA JUMAN UniDic IPA JUMAN UniDic VN+VN V(N)+V(N) V+V V+V V+V N+VN N+VN N+VN Adv+VN Adj+N * [38] (a) (b) (a) : (15) a. b. c. (15a) (15b) (15c) i ii i (b) : (16) a. ϕ b. ϕ? c 2013 Information Processing Society of Japan 9
10 c. ϕ? (16a) (16b) (16c) (17) (18) a. ( ) / b. ( ) / c. ( ) / d. ( ) NTC A B VA B V (19) a. [ ha ] [ ga ] / b. [ ga ] [ wo ] / c. [ ha ] [ ga ] / d. [ no ] [ ga ] (20) a. [ ha? ] [ ga ] b. [ ha ] [ ha? ] [ ga ] c. [ ha? ] [ wo ] d. [ ga ] [ ha? ] [ wo ] (19) (20a) (19) (20a)(20c) KTC NTC (21) a. [ ga2 ] [ ga ] b. [ ga2 ] [ ga ] c. [ ga2 ] [ ga ] d. [ out ] [ ga ] NTC KTC c 2013 Information Processing Society of Japan 10
11 (22 ) a b c d * 10 (22) a. [ ha ] [ ga/wo ] / (NTC ) b. [ ga ] [ wo ] / (NTC ) c. [ ga2 ] [ ga/wo ] / (KTC ) d. [ ga ] [ wo ] (KTC ) NTC (23) a. [ extra ga ] [ ga ] b. [ extra ga ] [ ga ] c. [ extra ga ] [ ga ] [ wo ] d. [ extra ga ] [ ga ] e. [ extra ga ] [ ga ] [ wo ] NTC / * 11 NTC 5.1 (24) a. [ extra ga ] [ ga ] b. [ extra ni?/benefactory(peripheral) ] [ *10 KTC () *11 NTC 1.5 wo] (25) a. / b. c. d. NTC KTC (i) NTC KTC (ii) (i) (25a)(25b) (25c) (ii) [41] OpenMWE [6] c 2013 Information Processing Society of Japan 11
12 (25d) KTC NTC 2 KTC NTC 2 (26) a b NTC (26) a. [ extra ga ] [ ga ] [ wo ] NTC b. [ ga ] [ wo ] NTC KTC (27) a. [ ni ] [ wo ] KTC b. [ ga ] [ wo ] NTC : KTC NTC 1 10 [27] KTC NTC KTC NTC c 2013 Information Processing Society of Japan 12
13 [15], [16] (28) a. [ ga ] [ ni ] b. [ ga ] (29) a. [ ni? ] [ ga ] b. [? ] [ ga ] A B A B (30) a. b. c. [ ga ] [ wo ] [ extra ga ] [ ga ] d. (31) a. b. c. d. (i) c 2013 Information Processing Society of Japan 13
14 (ii) (iii) 6 6 > > > (32) NTC KTC * NTC NTC BCCWJ [33] *12 NTC NTT [10] BCCWJ (33) a. b. (33a) Web (33b) (i) (ii) (i) (ii) c 2013 Information Processing Society of Japan 14
15 5.4 Wikipedia BCCWJ * 13 1,000 1, (34) a. - (35) a. b (36) a. b. NTC KTC *13 Yahoo!Yahoo! 5 (37) a. [ ga ] b. [ ga ] c. [ ga ] d. [ ga ] 6. 5 (5.1.1, 5.1.2, 5.1.3, 5.2.3, ) c 2013 Information Processing Society of Japan 15
16 (5.1.1, 5.1.3, ) 5.2.4, [25] (5.2.1, ) (5.1.1, ) [1] c 2013 Information Processing Society of Japan 16
17 7. NTC KTC 4 15 [1], [4] 6 [1] Bayerl, P. S. and Paul, K. I.: What determines intercoder agreement in manual annotations? a meta-analytic investigation, Comput. Linguist., Vol. 37, No. 4, pp (2011). [2] Burchardt, A. and Pennacchiotti, M.: FATE: a FrameNet-Annotated Corpus for Textual Entailment., Proceedings of LREC 2008 (2008). [3] Carreras, X. and Màrquez, L.: Introduction to the CoNLL-2005 shared task: semantic role labeling, Proceedings of the Ninth Conference on Computational Natural Language Learning, pp (2005). [4] Fort, K., Nazarenko, A., Rosset, S. et al.: Modeling the complexity of manual annotation tasks: A grid of analysis, Proceedings of the International Conference on Computational Linguistics (COLING 2012), pp (2012). [5] (1998). [6] Hashimoto, C. and Kawahara, D.: Construction of an idiom corpus and its application to idiom identification based on WSD incorporating idiom-specific features, Proceedings of the conference on empirical methods in natural language processing, Association for Computational Linguistics, pp (2008). [7] Hovy, E., Marcus, M., Palmer, M., Ramshaw, L. and Weischedel, R.: OntoNotes: the 90% solution, Proceedings of the human language technology conference of the NAACL, Companion Volume: Short Papers, Association for Computational Linguistics, pp (2006). [8] Iida, R., Komachi, M., Inui, K. and Matsumoto, Y.: Annotating a Japanese text corpus with predicate-argument and coreference relations, Proceedings of the Linguistic Annotation Workshop, Association for Computational Linguistics, pp (2007). [9] Iida, R. and Poesio, M.: A cross-lingual ILP solution to zero anaphora resolution, Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics, pp (2011). [10] Kawahara, D. and Kurohashi, S.: Case frame compilation from the web using high-performance computing, Proceedings of the 5th International Conference on Language Resources and Evaluation, pp (2006). [11] Kawahara, D., Kurohashi, S. and Hasida, K.: Construction of a Japanese Relevance-tagged Corpus., LREC (2002). [12] Kurohashi, S. and Nagao, M.: Kyoto University Text Corpus Project, Proceedings of the Annual Conference of JSAI, Vol. 11, pp (online), available from (1997). [13] Laparra, E. and Rigau, G.: Impar: A deterministic algorithm for implicit semantic role labelling, Proceedings of the 51st Annual Meeting of the Association for Computational Linguistics (ACL 2013), pp (2013). [14] Liu, D. and Gildea, D.: Semantic role features for machine translation, Proceedings of the 23rd International Conference on Computational Linguistics, Association for Computational Linguistics, pp (2010). [15] Loper, E., Yi, S.-T. and Palmer, M.: Combining lexical resources: mapping between propbank and verbnet, Proceedings of the 7th International Workshop on Computational Linguistics, Tilburg, the Netherlands (2007). [16] Loper, E., Yi, S.-T. and Palmer, M.: Semlink 1.1,, available from (accessed ). [17] Màrquez, L., Carreras, X., Litkowski, K. C. and Stevenson, S.: Semantic role labeling: an introduction to the special issue, Computational linguistics, Vol. 34, No. 2, pp (2008). [18] Matsubayashi, Y., Miyao, Y. and Aizawa, A.: Building Japanese Predicate-argument Structure Corpus using Lexical Conceptual Structure, Proceedings of the Eight International Conference on Language Resources and Evaluation (LREC 12) (2012). [19] Matsumoto, Y.: A syntactic account of light verb phenomena in Japanese, Journal of East Asian Linguistics, Vol. 5, No. 2, pp (1996). [20] Vol. 14, No. 5, pp (2007). [21] Meyers, A., Reeves, R., Macleod, C., Szekely, R., Zielinska, V., Young, B. and Grishman, R.: The NomBank project: An interim report, HLT-NAACL 2004 workshop: Frontiers in corpus annotation, pp (2004). [22] Moor, T., Roth, M. and Frank, A.: Predicate-specific Annotations for Implicit Role Binding: Corpus Annotation, Data Analysis and Evaluation Experiments (2013). c 2013 Information Processing Society of Japan 17
18 [23] (1989). [24] Palmer, M., Kingsbury, P. and Gildea, D.: The Proposition Bank: An Annotated Corpus of Semantic Roles, Computational Linguistics, Vol. 31, No. 1, pp (2005). [25] Pradhan, S. S., Loper, E., Dligach, D. and Palmer, M.: SemEval-2007 task 17: English lexical sample, SRL and all words, Proceedings of the 4th International Workshop on Semantic Evaluations, Association for Computational Linguistics, pp (2007). [26] Ruppenhofer, J., Ellsworth, M., Petruck, M., Johnson, C. and Scheffczyk, J.: FrameNet II: Extended Theory and Practice, Berkeley FrameNet Release, Vol. 1 (2006). [27] Sasano, R., Kawahara, D., Kurohashi, S. and Okumura, M.: Automatic Knowledge Acquisition for Case Alternation between the Passive and Active Voices in Japanese, Proceedings of EMNLP 2013 (to appear) (2013). [28] Shen, D. and Lapata, M.: Using Semantic Roles to Improve Question Answering., EMNLP-CoNLL, pp (2007). [29] Silberer, C. and Frank, A.: Casting implicit role linking as an anaphora resolution task, Proceedings of the First Joint Conference on Lexical and Computational Semantics - Volume 1: Proceedings of the main conference and the shared task, and Volume 2: Proceedings of the Sixth International Workshop on Semantic Evaluation, pp (2012). [30] Taira, H., Fujita, S. and Nagata, M.: A Japanese predicate argument structure analysis using decision lists, Proceedings of the Conference on Empirical Methods in Natural Language Processing, Association for Computational Linguistics, pp (2008). [31] Yoshikawa, K., Asahara, M. and Matsumoto, Y.: Jointly Extracting Japanese Predicate-Argument Relation with Markov Logic, Proceedings of the 5th International Joint Conference on Natural Language Processing, pp (2011). [32] GDA 0.74, [33] BCCWJ 22 pp (2011). [34] (1991). [35] ipadic version 2.6.3, [36] 8 pp (2002). [37], guideline.pdf [38] Vol. 2, (2009). [39] 15 pp (2009). [40] 18 pp (2012). [41]. Vol. 2007, No. 35, pp (2007). [42] , ryui/coreference tag.html [43] : NAIST Vol. 17, No. 2, pp (2010). [44] 15 pp (2009). c 2013 Information Processing Society of Japan 18
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RD-003 Building a Database of Purpose for Action from Word-of-mouth on the Web y Hiromi Wakaki y Hiroko Fujii y Michiaki Ariga y Kazuo Sumita y Kouta Nakata y Masaru Suzuki 1 ().com 1 Amazon 2 3 [10] 2007
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Acquiring Organized Information from News by Incremental Theme Refinements 1 1 1 Yutaro Taniguchi 1 Tetsunori Kobayashi 1 Yoshihiko Hayashi 1 1 1 School of Science and Engineering, Waseda University Abstract:
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