表現学習時代の生成語彙論ことはじめ
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表現学習時代の生成語彙論ことはじめ

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生成語彙論の入門と、単語の表現学習、compositionalityの学習に関する入門です

生成語彙論の入門と、単語の表現学習、compositionalityの学習に関する入門です

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表現学習時代の生成語彙論ことはじめ Presentation Transcript

  • 1. 2014/10/16 PFIVZX^ ¿Ó½Ǝ»: —ÐŇǖĦ!5;&D ĉPreferred Infrastructure Ù¦Ʋǁ (@unnonouno)
  • 2. ƝLJŘ Ù¦Ʋǁ (@unnonouno) ! ŪåŇĭ¸GdVfuSh€XGÁnj½Ǝ ! ĘƬĭ¸E/H05GKA' ! “‚ú߸ýŵġIBMôLjŎPFI 8
  • 3. mrep5c}P1KA%- ! řĹƑƚ8›%3ÖĨåŇ4íƾ4A' ! pip install mrep 4S€f} 9
  • 4. Ÿ§:Ú ! word2vecP†ù8ƄŇ:¿Ó½ƎŹK:;7%P%A %- :
  • 5. ¿Ó½Ǝ:ÚPň3Ĉ0-!5  ƣƵ.5ăJM3LƄ Ň:+&)PrWf} Į :†8ƅ%ñDJM L:4;7  ;
  • 6. —ÐŇǖĦ Generative Lexicon (GL) <
  • 7. ®:£Ć ! —ÐŇǖĦ813:ƴƄ7šʼn ! ¿Ó½Ǝ5Êů:Ð5:¨Ē 18EA%3Œ:Ú OJ7,  =
  • 8. The Generative Lexicon [Pustejovsky95] ! James PustejovskyĀdž ! ÄƸA4;ƟDA)Q4% - ! TimeML:ĀdžŽ4EĐL ! „Å; ¿Ó813:ÚP %Iƙ03-:4<0K %- > ÊÌ5¥% http://www.cs.brandeis.edu/~jamesp/
  • 9. „Ň:„7J·¦é—:„ [·¦05] ! ·¦ǍƆ—ÐŇǖÊů Ħ ! ®ƟQ4LǕƥ† ; _ ; ?
  • 10. Æ8ħă8%-´ē ! ·¦ǍƆ—ÐŇǖÊůĦ[·¦05]:Û12 ƽ ! James Pustejovsky, Introduction to Generative Lexicon. [Pustejovsky05] ! ě„ƲëGenerative Lexicon:NjÇ [ě„ 06] 76
  • 11. ɋ:Êů813ă3BI ƛŸ:8‹0- ŒP8ƍ- ¥ƺ48‹0- ! ‰č8ɋ5å03EĬî5%3:ɋ5æŲ 5%3:ɋL 77
  • 12. gR:Êů813ă3BI Ps€V4Ǒ0- Jš03«# ! wj5%3:gR5‹Ò'L”Ï5%3:gR:Ê ůL ! é:ɋ:ŗ5™&I7!5ĸ!037 
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  • 14. ! ă3BL5ƄŇ;1:ƌ7LĎćP â03L!58Ñ2 ! ċOMœ8I03ÊůģO03L ! !:Êů:ģµ8;ęª:ĨƏÎ:I7E: ĐL ! %Eƌ7LåŇ4Eǃ-ÓłL  79
  • 15. —ÐŇǖĦ:ăœ ! 1:Ňǖ8ęª:ļŋPâ03L ! đǓ8Ī&3+:ļŋJƦ§ƌ7L Êů—Ð#M3L5ăL 7: ɋ Ĭî:ɋ æŲ:ɋ $_
  • 16. ŅÊ ™ŸƌĺŇ5êĺŇ;ĔĖ#ML ! êĺŇ;Êů¢8ŒJ:¨ĒPâ03LÔ çÇ ! -A-A™&Ÿ870-Ň;™ŸƌĺŇ5% 3ĔĖ#ML 7;
  • 17. Ù¦;7*!ÚÝ8ŰůPâ03L Ī¹‡ƄŇGƣŇ~r}:ÊůPA Ʊ7Ë݉ŏê5ă3L %( ¿þņ6™&Êů %( ¿þ™&.6ņÊů 7<
  • 18. Ňǖ:ĝŃļŋWU|Rļŋ5E:P ăL ŇPń­'LƠÎGł:ğ 1. ļÐWU|RConstitutive ! ƋēG£Ć76Œ4ˆÒ3LPā' 2. řĚWU|RFormal ! +MŒ7:‡ì:NjōPā' 3. ²¢WU|RTelic ! ÁĊG²¢Pā' 4. ƱWU|RAgentive ! +MP—Bˆ'¾ÿGÄƉPā' 7=
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  • 20. ŗ ò:WU|Rļŋ 7? 1. ļÐ `Syǀ k€g}  2. řĚ ŀKîÁ nj  3. ²¢ ŀLĄĩ 'L  4. Ʊ æB©3L ÿL  @1AKN`KBC0 L4GM*!J&DIBQS[^T
  • 21. Œ4!%-úßĠÇ7:
  • 22.  ŔŌ:ò;ş ŔŌ:ò;ngş ! ò;Ŋ¾'L5ƿǏ:Ƥø!!4; ²¢WU|RĐL ! +:-D…;«:đ:Êů.5øDŽ4 L 86
  • 23. Ƈő ƿǏ:ƤøPįŁ'L5Y€f87L
  • 24.  ƭǎ ä4Dž3-Q.I Ɯö4 lhtS 
  • 25. 60/
  • 26. ä4
  • 27. Ɯö4
  • 28.  ƭǎ .Jä:†8LƜö:†.I  ! Ɯö;ä8LE:5ƿǏ:ƤøPįŁ%3L ! ƶ8ärbg8703-Jƭǎ:^| o;­J8ÀŪ 1Ƨ:åŇĭ¸5:PGK-9  87 ^[]U5@CLASSICAOP
  • 29. 7Q4WU|RļŋPăL:
  • 30.  ! ê:ƄŇ:Êů8¨%3é8•-I7ƿǏ:• øūĢ'L ! +:-D-Eáơ#M-:I7¿Ó4Êů ª0-K+0K7đĖ:Êů87L!5ĐL ! !:ƿǏ:•øJ³ï:đ†4:Êů—Ð# ML:4;7  88
  • 31. begin8;į×:Êů—Ð#ML begin the meeting begin a dance begin the book begin the movie ! +E+Ebegin:58;‹ƒGł4;
  • 32. ! beginį×:ÊůPâ03L5ĈIKđǓ8Ī &3Êů—Ð#ML5ăL?Ū 89
  • 33. ęÐco-composition begin
  • 34. the book 1. begin:žN8;łÒL;(.book;ł4 ;7 , 2. bookPł5%3øDŽ%I`SqÍÈ 3. WU|RJúßPÂ03L ‰¶:—Ðq^P 5Ž= 8:
  • 35. cf. ƿǏ:ŝģŶ double x =
  • 36. 10 1. double:žN8;double:ŞÒL;(.10; double4;7 , 2. 10Pdouble:Ş5%3øDŽ%I 3. Vxf:œ¯:úßPÂ03L ‰¶:—Ðq^P13*",5Ž= 8;
  • 37. ħă ³;—ÐŇǖĦ8;ĴK31:ļŋL  ĝŃļŋ;—ÐŇǖĦ:41ļŋ:†:11 ! Ƴļŋ ! łļŋ ! ĝŃļŋ ! Ňǖżƕļŋ ®;ėŷ%A'I 8<
  • 38. !!A4:A5D ! ĥŇǖ8;+:ċOMœ8¨'LúßPâ0 3LWU|Rļŋ ! ŹŴ:ƄŇ5śćªK:øDŽ478 !:WU|R:úßPċ03¥%ÊůP—Ð 'LęÐ 8=
  • 39. ŪåŇĭ¸:†4—ÐŇǖĦ;6MJċOM 3-
  • 40.  ! åŇĭ¸½ƒ:«430÷ ! ACL:«4300÷ 8> ÊÌ5Ĥ7
  • 41. 
  • 42. /H05!M;‚ģ  ! 11:Ňǖ4!MJ:úß 5 . $./LHE , @A M5BAM
  • 43. +3 8? 45. $.#/R%BFSY]W2M( $
  • 44. WU|Rļŋ;‚ĨũdVfJ¾Ʈõ%- ! Web:íƾóČJ…’4ÿÐ%-m`€ Pܹ%3ǐˆ'Lœ¯ [Cimiano+07] ! ęĸǔ°5ðǒG¾ǒ:ƠÎPĝƯ8%3{ €V€X½ƎPƂ¹'Lœ¯ [ĻŖ+12] 5;ċ:EƴƄ4;7#+  96
  • 45. Ĥ%ƖJ•7%3BL  ! ƄŇ6:I7ƃ:ƄŇ5‰Ƽ8ċOML 5!58›'LüŭP±ųµ%3L ! 6:I7ƄŇ5ċOML8I03ƄŇ: ÊůEģOL 97
  • 46. !:Ú6!4  Ÿ§: Statistical Semantics:Ú8ǃ3L 98
  • 47. !!4‰°—ÐŇǖĦJŮM3 Êů:Ð:ÚP%A' 99
  • 48. Statistical Semantics:#J Statistical Semantics is the study of "how the statistical patterns of human word usage can be used to figure out what people mean, at least to a level sufficient for information access”(ACL wiki) ! ŹŴƄŇ:ˆÓǔ°76:IJè¢7ÎŃJ+:Ň: ÊůPăL ! ‹ƚ‘øGhz{}ibf76:’¯¹JML 9:
  • 49. ƄŇ:rWf}¿Ó ! Ÿ§:Ú;ƄŚ:ƄŇ:ÊůP¿Ó%- ! ®§;ŹŴƄŇ5:¨Ē4ÊůģOLÚ7: 4/(J7Lo~]:Êů67 L:
  • 50. 9;
  • 51. —ÐŇǖĦ5Statistical Semantics:¨Ē ! —ÐŇǖĦ ! ĝ¡:đǓ8LƄŇ:ˆÓ:ÊůPă3L ! 5+:I7ģµPĸ!'-D:Ňǖ:ļ ŋPă3L ! Statistical Semantics ! ŹŴƄŇ:‘Ɯ8I03‰Ɣ¢7+:ƄŇ:Êů Pă3L ! ƀ±¢7ƄŇ:ˆÓ8›'LÊů8åſ%37 ®J'LI 9<
  • 52. Principle of compositionality (Frege1892] … the meaning of a complex expression is determined by the meanings of its constituent expressions and the rules used to combine them (wikipedia
  • 53. )       
  • 54.   9=
  • 55. ·Š#Q:{SgA5A03L https://speakerdeck.com/mamoruk/a-tensor-based-factorization-model-of-semantic-compositionality 9>
  • 56. ¿ÓrWf}:Ð;ĵ%ĕIKƻĕķ [Mitchell+08] ! ĵ%ĕGƻĕ76rWf}:Ðœ¯Pılj ! ÇƑ"5:ƻĕMultiplicative¬0/F0- 9?
  • 57. Statistical Semantics5:¨Ē ! Statistical SemanticsŸ§:£Ć;6/J 5å5#-(:rWf}PƮõ'LŎŠ ! Compositionality:ŎŠ;+:rWf}: :ŎŠ ĞœP™8øœØEL%¿Ó½Ǝ:ˆÓ 4ƁK‡KP•)3L :6
  • 58. Êů:ÐP‹ƚ4¿Ó'L (MV-RNN) [Socher +12] ! ĥƄŇ8;rWf}5‹ƚ›Ī'L ! ŵƹ#ML5ƪ:‹ƚP¼’:rWf}8ƻ3 #J8žĶř7ģŶ f PŦż¢8‹ ! RootA4ƗKľ'5đ:¿ÓrWf}õJML :7
  • 59. GGd€_}. [Cruys+13] ! ÆŇ¾ǒ²¢Ň:31Pd€_}Pċ03æ) 3L:.5ăL :8
  • 60. Dynamic Convolutional Neural Network [Kalchbrenner+14] ! CNNPċ03ƄŇ:A5AKPæB‡ 3 ! ļđÞ4;7Żǃ:ŜČõJML
  • 61.  :9
  • 62. Ƈő CNN5compositionality ! Ŀ~Sy4;ŧD3ijÏ¢ƄƷ7úß ! ˜Ă:~Sy87L8¶M3+MJæBO#K IKƣƵ7Êů:LúßPûŭ%3L :: Layer1 Layer3 Layer5 [Zelier+14]OP'
  • 63. åŇĭ¸;ĸÔņ  4 nW^}Tb[¤‘ǂ źřŸƑƄŇ–Ú ¿Ó
  • 64. ƄŇo~]đ ‘ø'LæB‡ L M- :; M-
  • 65. !:œŐ8—ÐŇǖĦ:ü•Pď)7  ! —ÐŇǖĦ;CompositionalityP…’4űƘ% 3±ų2L-D8Ľ¸#M-¸Ħ5•M7 
  • 66. ! šƕ½Ǝ76:m{aSvZofĸ+7 ®!+ĜŨ:ü•GŹŴ‘¦P•ą'> :<
  • 67. Ãà:Ú ƣƵ.5ăJM3LƄ Ň:+&)PrWf} Į :†8ƅ%ñDJM L:4;7  :=
  • 68. ęÐP¿ÓrWf}85K!C [Tsubaki+13] companyM JMrun run companyM)" run LOQ ! ƪƪ8ŕŢPſ@%3¥%rWf}PÿL ! 4-rWf}JÊů:Ð‹OML :> run companyM Mrun company LOQ runM JMcompany Mcompany '48 
  • 69. ƄŇ:Ð8›'L1:ŁÔ ! —ÐŇǖĦ ! åŇÓłPűƘ%3Awe}µ%I5'L īB ! Ť:׸we} ! űƘ#M-åŇe`P‡’ń­'LI7we }:ŬƘ ! ¿Ó½Ǝųšƕ½Ǝų ! ļÐ5¿Ó:½ƎP™8‹5%3L !MJ:RSeR;ƞţ8¨Ē%3L :?
  • 70. A5D ! —ÐŇǖĦ5;
  • 71. ! Ňǖ;8›'LÀƊº7üŭJđǓ8Ī&3Ê ů—Ð#ML5ăL ! Ň:Êů:Ð8¨'LŎŠ ! ƄŇ:¿ÓrWf}PÐ%3ƣ¿Ó:ÊůP ÿL ! ¿Ó½Ǝpv8ŀ03®İ‹03L åŇ½:ü•5åŇĭ¸:¥%’¯:㏠E05ÕC
  • 72. ;6
  • 73. "ƓƢK5"$A%- ;7
  • 74. ħăđƫ (1/3) ! [Pustejovsky95] James Pustejovsky. The Generative Lexicon. MIT Press. ! [·¦05] ·¦ǍƆ. (4+$. N%ˆư ! [Pustejovsky05] James Pustejovsky. Introduction to Generative Lexicon. Foundations of SemanticsƩĺ´ē. http://www.cs.brandeis.edu/~jamesp/classes/LING130/ ! [ě„06] ě„Ʋë. Generative Lexicon2. Ɛ:ğ†NJ̓:ŏÌƈ ;8
  • 75. ħăđƫ(2/3) ! [Cimiano+07] Philipp Cimiano, Johanna Wenderoth. Automatic Acquisition of Ranked Qualia Structures from the Web. ACL2007 ! [ĻŖ+12] ĻŖ˜ƨ, ·Šť, ě„Ʋë. (4$ (!'&)
  • 76. 
  • 77. . 0. NLP2012. ! [Mitchell+08] Jeff Mitchell, Mirella Lapata. Vector-based Models of Semantic Composition. ACL2008. ! [Socher+12] Richard Socher, Brody Huval, Christopher D. Manning, Andrew Y. Ng. Semantic Compositionality through Recursive Matrix-Vector Spaces. EMNLP2012. ;9
  • 78. ħăđƫ(3/3) ! [Cruys+13] Tim Van de Cruys, Thierry Poibeau, Anna Korhonen. A Tensor-based Factorization Model of Semantic Compositionality. NAACL2013. ! [Kalchbrenner+14] Nal Kalchbrenner, Edward Grefenstette, Phil Blunsom. A Convolutional Neural Network for Modelling Sentences. ACL2014. ! [Zelier+14] Matthew D. Zeiler, Rob Fergus. Visualizing and Understanding Convolutional Networks. ECCV2014. ! [Tsubaki+13] Masashi Tsubaki, Kevin Duh, Masashi Shimbo, Yuji Matsumoto. Modeling and Learning Semantic Co-Compositionality through Prototype Projections and Neural Networks. EMNLP2013 ;: