19
N-gram統計量からの係り受け情報の復元 プリファードインフラストラクチャ 海野 裕也, 岡野原 {unno, hillbig}@prefered.jp

N-gram統計量からの係り受け情報の復元 (YANS2011)

Embed Size (px)

DESCRIPTION

 

Citation preview

  • 1. N-gram2011/09/22 NLP 6 ,{unno, hillbig}@prefered.jp

2. l Nll l 3. l l 4. ll ll 5. lllllll N 6. l lll ll llll l 7. Eisner[Eisner96] A B C DE root = AD + BD + B C+ Droot + D El TS(T)l S(T) = (m, h) T s(m, h)l (m, h) T l S(T) Topt O(n3) 8. Google N-gram PMIl Google Nl #(mh) m, hl #(m) ml Eisner s(m, h)T const 9. 10. 1. ll2.ll 3.ll l 11. 1.lll l PMIl580K 117M72Kl580K 13.4M20.5K 12. 2.l ll542M114M 68Kl542M1.66M77l 13. 3. l ll 14. 1 l PMIl 15. 1 2l l 16. 2lll 17. [ 05][ +06] (1)101101010001(2) 0.95 0.05 0.95 0.95 0.05 0.95 0.05 0.95 0.05 0.05 0.05 0.95(3) 0.99 0.01 0.99 0.89 0.18 0.85 0.19 0.95 0.00.00.0 0.99 (1)(2) SSC ( =0.95) (3)lll 18. PMI [Zhou+11]l PMIl PMIGoogle l +1 ~ 2 19. l [Eisner96] J. M. Eisner. Three New Probabilistic Models forDependency Parsing: An Exploration. COLING 96.l [ 05] . . 05.l [+06] , , . . NLP 06.l [Zhou+11] G. Zhou, J. Zhao, K. Liu, L. Cai. Exploiting Web-Derived Selectional Preference to Improve StatisticalDependency Parsing. ACL 11.