{ "paper_id": "O04-1012", "header": { "generated_with": "S2ORC 1.0.0", "date_generated": "2023-01-19T08:00:16.797495Z" }, "title": "", "authors": [], "year": "", "venue": null, "identifiers": {}, "abstract": "", "pdf_parse": { "paper_id": "O04-1012", "_pdf_hash": "", "abstract": [], "body_text": [ { "text": "\uf906 polysemous word \uf92d \uf906 HowNet \uf94e selectional preference \ufa01 \uf9d0 \uf9a8 w \u03c0 \uf9d0 HowNet ) , ( \u03c0 \u03bd w f w \u03c0 \uf96b \u03bd \uf961 \u03c0 w \uf9d0 ) (w f v w \uf96b \u03bd \uf961 \uf967 \uf9d0 w \u03c0 selectional preference \ufa01 (1) ) ( ) , ( ) , ( w f w f w A \u03bd \u03bd \u03bd \u03c0 \u03c0 = (1) \uf9be w \uf96b \u03bd \uf967\uf941 w ) (w f v \uf94f 1 \uf9a8 s w \u03bd } , , , { ) ( 2 1 y s \u03c0 \u03c0 \u03c0 K = \u03a0 s \uf9d0 \uf9be w s \uf96b \u03bd ) (s \u03a0 \u2208 \u03c0 ) , ( \u03c0 \u03bd w f \uf969 y / 1 1 3 eat tell find HUMAN FOOD \uf978 \uf9d0 \uf9be 1 eat \uf9d0 FOOD", "cite_spans": [], "ref_spans": [], "eq_spans": [], "section": "", "sec_num": null }, { "text": "\u2126 w WordNet n \uf9a8 } , , , { \u03b8 \u03b8 \u03b8 K = \u0398 w w i \u03b8 WordNet i m \uf967 w i \u03b8 } , , , { , 2 , 1 , i m i i i i \u03bb \u03bb \u03bb K = \u039b w i \u03b8 MINIPAR \uf906 T w \uf906 T \u00b5(T) \uf9a8 } , , , { ) , ( ), ( , 2 , 1 T T T T w T \u00b5 \u03c8 \u03c8 \u03c8 K = \u03a8 T w T k , \u03bd T w T k , \u03c8 } , , , { ) , ( ), ( , 2 , 1 T T T T w T \u00b5 \u03bd \u03bd \u03bd K = \u0393 w T k , \u03c8 w i i \u03b8 j j i, \u03bb \uf969 \uf9dd (1) j i, \u03bb T T k , \u03c8 selectional preference \ufa01 \u2211 = ) ( 1 , , ) , ( ) ( 1 , T k T k j i T k A T \u00b5 \u03bd \u03c8 \u03bb \u00b5 i \u03b8 \uf969 i \u03b8 \uf969 \u2211 \u2211 = \u2126 = = ) ( 1 , , 1 ) , ( ) ( 1 1 ) , | ( , T k T k j i m j i i t T k i A T m T w \u00b5 \u03bd \u03c8 \u03bb \u00b5 \u03b8 (2) (2) \uf906 T w i \u03b8 \uf969 selectional preference \ufa01 ) , ( , , , T k j i T k A \u03c8 \u03bb \u03bd \uf969 t \u2126 \uf978 \uf969 \uf918 0 1 WordNet \uf9b5\uf906 \uf9b5\uf906 \uf906 \ufa01 \uf906 \uf9dd \uf906 \uf9a8 T S w \uf906 w i \u03b8 \uf9b5\uf906 \uf99c 3 i \u03b8 \uf9b5\uf906 \uf969 s \u2126 \uf9b5\uf906 (3) i \u03b8 \uf9b5\uf906 \uf969 \uf969 (\u03b8 i | w,T) 1. w T S ) , ( w T \u03a8 ) , ( w S \u03a8 w ) , ( w T \u0393 ) , ( w S \u0393 } , , , { ) , ( ), ( , 2 , 1 T T T T w T \u00b5 \u03c8 \u03c8 \u03c8 K = \u03a8 } , , , { ) , ( ), ( , 2 , 1 S S S S w S \u00b5 \u03c8 \u03c8 \u03c8 K = \u03a8 } , , , { ) , ( ), ( , 2 , 1 T T T T w T \u00b5 \u03bd \u03bd \u03bd K = \u0393 } , , , { ) , ( ), ( , 2 , 1 S S S S w S \u00b5 \u03bd \u03bd \u03bd K = \u0393 2. T w T j, \u03c8 S w S k, \u03c8 S k T j , , \u03bd \u03bd = T j, \u03c8 HowNet T j n , \uf9d0 } ,..., , { ) ( , , , 2 , , 1 , , , T j n T j T j T j T j \u03c0 \u03c0 \u03c0 \u03c8 = \u03a0 S k, \u03c8 HowNet S k n , \uf9d0 } ,..., , { ) ( , , , 2 , , 1 , , , S k n S k S k S k S k \u03c0 \u03c0 \u03c0 \u03c8 = \u03a0 ) ( ,T j \u03c8 \u03a0 \uf9d0 l T j , , \u03c0 ) ( ,S k \u03c8 \u03a0 \uf9d0 m s k , , \u03c0 m S k l T j , , , , \u03c0 \u03c0 = \uf9d0 \uf94f \uf969 ) , ( T M i \u03b8 T j n , / 1 ; 0 ) , ( = T M i \u03b8 unmatched; as ) , ( all mark , w T T j \u0393 \u2208", "cite_spans": [], "ref_spans": [], "eq_spans": [], "section": "", "sec_num": null }, { "text": "EQUATION", "cite_spans": [], "ref_spans": [], "eq_spans": [ { "start": 0, "end": 8, "text": "EQUATION", "ref_id": "EQREF", "raw_str": "< = m n m m S k T j i i m S k l T j n T M T M , , , , , 1 ) , ( ) , ( ) ( if + = = \u03b8 \u03b8 \u03c0 \u03c0 } 3. (3) \ufa01\uf97e \uf906 \uf9b5\uf906 \uf969 ) ( ) , ( ) , | ( T T M T w \uf969 (3) ) , | ( T w i s \u03b8 \u2126 \uf9b5\uf906 \uf969 \uf974 \uf969 (4) threshold \uf906 T w \uf969 \uf974 ) , | ( T w i t \u03b8 \u2126 ) , | ( T w i s \u03b8 \u2126 \ufa01\uf967 \uf967 \uf961 \uf906 6.1 \uf941 \uf967 \uf961 ) , | ( ) , | ( max arg T w T w i s i t i i \u03b8 \u03b8 \u03b8 \u2126 + \u2126 \u0398 \u2208 (4) 5 \uf94e \uf9ba \uf974 \uf967 \uf967 \ufa22 \uf94e\ufa05 \uf9e0\uf96b \uf9fc \uf967 \uf906 \uf9e0 \uf976 culture-dependent \uf976 \uf98a \uf9ba [12][18] \u03c1 \u03c1 n n m n ] 10 / , 10 / [ n m n m + \u2212 \ufa01 fitness \ufa01 \uf9d0 \uf9d0 collocation \uf9d0 HowNet \u2211 \u2260 \u03a0 \u2229 \u03a0 \u2135 = \u03a0 \u03b7 \u03c6 \u03ba \u03ba \u03b7 S w w S } ) ' ( ) ( and contains | 1 { 1 )) ' ( Pr( \u2211 \u2260 \u03a0 \u2229 \u03a0 \u2135 = \u03a0 \u03b7 \u03c6 \u03c7 \u03c7 \u03b7 S i i t S t )) ' ( ), ( Pr( i t \u03a0 \u03a0 \u03ba \uf9be \u03b7 S w ) (w \u03a0 ) (\u03ba \u03a0 ) (\u03c7 \u03a0 ) ' ( i t \u03a0 \uf967 \uf9b5 } ) ' ( ) ( and ) ( ) ( and where , contains | 1 { 1 )) ' ( ), ( Pr( \u03c6 \u03c7 \u03c6 \u03ba \u03c7 \u03c7 \u03ba \u03b7 \u03b7 \u2260 \u03a0 \u2229 \u03a0 \u2260 \u03a0 \u2229 \u03a0 \u2260 \u2135 = \u03a0 \u03a0 \u2211 S i i t w w w S t \ufa01 (5) \u2211 \u2208 \u03a0 \u03a0 \u03a0 \u03a0 \u2212 = T t i i i t t q f ' )) ' ( Pr( )) ( Pr( )) ' ( ), ( Pr( log ' 1 ) ( \u03ba \u03ba \u03ba (5) \uf974 ) (\u03ba f 0.3 \uf9ba collocation \uf969 0.3", "eq_num": "(5)" } ], "section": "", "sec_num": null } ], "back_matter": [], "bib_entries": { "BIBREF0": { "ref_id": "b0", "title": "A preliminary inquiry into using corpus word frequency data in the automatic generation of English language cloze tests", "authors": [ { "first": "D", "middle": [], "last": "Coniam", "suffix": "" } ], "year": 1997, "venue": "Computer Assisted Language Instruction Consortium", "volume": "16", "issue": "2-4", "pages": "15--33", "other_ids": {}, "num": null, "urls": [], "raw_text": "D. 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3\uf9be\uf92d
\uf9be\uf9dd\uf937web crawlerTaiwan Journal
1 <http:/\uf901 \uf94e \uf9b5 \uf906 \uf92d \uf9e0\ufa01 item \ufa01 facility \ufa01 item discrimination [12] \uf961 \ufa0a \uf9be 163,719 \uf906 \uf9ba 3,077,474
\uf901 \uf9d0 \uf906\uf976 \uf974 word token HTML \uf906 \uf9dd\uf967 \uf918 MXTERMINATOR [1][4] word sense disambiguation word type collocation selectional preference [10] 31,732 \uf9ba \uf92d \uf92d \uf9f7\uf9a8 \uf92d Reynar\uf9be \uf9ba \uf906\uf9ba \ufa00 \uf906\ufa01
MXTERMINATORBrownWall Street Journal\uf9be97.5%\uf906\uf961
2 selectional preference [15] 4 \uf9be \uf9be\uf906\uf94e MXPOST \uf9dd lemma\uf9ca Pen Treebank 3 \uf92d \uf94e \uf976 \uf9b5 \uf974 classified \uf906 \uf961\uf9be5 \uf9dd Ratnaparkhi [13] VBNMXPOST collocation 6
classify \uf974 MINIPARJJ arrive at in order to \uf967 classified 2Lin MINIPAR [8]\uf906\uf967
\uf94e\uf9be MINIPAR\uf906\uf9ba\uf974\uf906partial parseMINIPAR
\uf9dd\ufa08\uf965w\uf906w
wsignal wordsignal
\uf98c\uf94e1 \uf906\ufa26\uf941\uf94e[18]
\uf98e\uf92dcomputer-assisted item generation CAIG [2][6] \uf9dd 2 \uf94e\uf906item pools \uf98a\ufa08
2\uf97e \uf94e\uf9b5\uf94e\uf98a Jimmy builds a grand building \uf906 \uf92d \uf9ba \uf978 \uf978
buildgrand \ufa26[11] \uf906\uf937 \uf9be\uf97e target sentence retriever building\uf937
\uf906\uf961\uf97e \uf9betagged corpus\uf941\uf94e\uf9dd\uf906\uf9e4 natural language item
processing specification \uf974\uf937\uf961\uf94e\ufa22cloze item 3 \uf95a
\uf9e4\uf9b5\uf906\ufa08\ufa08\uf94e WordNet <http://www.cogsci.princeton.edu/wn/> \uf97e
\uf906template-base target-dependent item requirements\uf9f7\uf906 [3] \uf9d0class\ufa22 selectional preference collocation \uf92d \uf9f7\uf906
[2]\ufa01\uf9b5\uf967\uf9be College Entrance Examinations LDC <http://www.ldc.upenn.edu/> \uf94e HowNet <http://www.keenage.com\\verb>OTA
<http://ota.ahds.ac.uk/> \uf969 7\ufa08 \uf9f7 28\uf9be [18]\uf906\uf92d \uf9f7\uf9ba
\uf906\uf92d\uf9e0 [16]\uf9dd\uf967 4\uf937\uf97e \uf906\uf906\uf9e4\uf984\uf969\uf97e
\uf906 2\uf906\uf94e\uf9be\uf965\uf906\uf906candidate
target sentence\uf906\uf9dd MXPOST
\uf9e0\uf98a\uf9ba\uf906\uf9e4\uf92d\uf906 item generator\uf965
multiple-choice\ufa08\uf94e\uf9ba\ufa0a selectional preference\uf94e\uf9a3
\uf94eJohns [7]Steven [17]concordancecollocation\uf9a3
\uf9beConiam [1] 4.1\uf9be Selectional Preference word frequency\uf9d0
2003 \uf98e \uf9be \uf9dd selectional preference \uf94e \uf969 \uf906 keyword matching 1 \uf9ba \uf94e key \uf94e \uf937 \uf906 3 collocation selectional preference \uf96b \uf937 \uf92d \ufa08 \uf92d [4][18] \uf9e4 \uf9d0 Selectional preference concordancer \uf97e \uf94e \uf9b5 \uf906 distractor \uf92d \uf906 target sentence \uf9b5 \uf96f chair \u57b7 \uf906 Susan interrupted the chair stem \uf967 distractor generator \uf98a \uf906 \ufa00 \uf9b5 \uf99a\uf905 \uf906 3 [10][14]\uf9dd\uf906
", "num": null, "text": "/taiwanjournal.nat.gov.tw> Taiwan Review China Post " } } } }