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Table 4.3. The Result of Description Type Annotation.Gardening Healthcare Economy Society Politics Law TotalAnalysis 4/.01 8/.02 3/.01 3/.01 5/.01 0/.00 23/.01Fact 94/.26 108/.25 103/.42 164/.37 199/.36 158/.43 826/.34Instance 92/.25 102/.24 52/.21 106/.24 87/.16 58/.16 497/.21Def 1 4/.01 6/.01 19/.08 8/.02 13/.02 4/.01 54/.02OoT 2 0/.00 0/.00 1/0.00 4/.01 21/.04 0/.00 26/.01Process 34/.09 2/.00 2/.01 10/.02 0/.00 20/.05 68/.03Co-Rea 3 15/.04 32/.08 2/.01 14/.03 44/.08 38/.10 145/.06P-P 4 3/.01 9/.02 1/.00 4/.01 4/.01 3/.01 24/.01Ca-Res 5 15/.04 20/.05 9/.04 25/.06 46/.08 25/.07 140/.06P-S 6 51/.14 55/.13 7/.03 41/.09 44/.08 31/.08 229/.10Comp 7 24/.07 27/.06 6/.02 11/.02 41/.07 5/.01 114/.05Others 25/.07 57/.13 43/.17 54/.12 52/.09 27/.07 258/.11Total 361 426 248 444 556 369 2404The rate of the assigned description types is similar in each domain. However,there are some description types in which the frequency is distinctively high comparedto the other domains such as the definition type in the economic domain,and process types in the gardening domain and legal domain.I evaluated the agreement between two tagging experts using kappa statistics.As in this experiment, the experts could place several tags, and a kappa value wascalculated for each tag type. The kappa statistics was described in next section.1 Definition2 Order-of-Time3 Conclusion-Reason4 Phenomenon-Problem5 Cause-Result6 Problem-Solution7 Comparison56
Table 4.4. Categorization of n Objects and m Categories.CategoryObject 1 2 . . . j . . . m1 n 11 n 12 . . . n 1j . . . n 1m S 12 n 21 S 2...i n i1 . . . n ij . . . n im S i...n n n1 . . . n nj . . . n nm S nC 1 C 2 . . . C j . . . C m4.3.5 The evaluation of agreement using Kappa statisticsKappa statistics has been used in previous studies in discourse analysis and textsummarization [18, 126, 140]. The kappa value is defined by a formula 4.1 whichmeans subtracting chance agreement from observed agreement.kappa value =P (A) − P (E)1 − P (E)(4.1)Here, P (A) is the proportion of times that the annotators agree and P (E) isthe proportion of times that I would expect the annotators to agree by chance.The kappa value is found as determined by the following process below. Considera dataset of n question articles, each of which is to be assigned to one of mquestion types.Each of a group of k annotators classifies each article into aquestion type. The assignments would be represented in Table 4.4 where n ij isthe number of annotators assigning the ith article to the jth question type. Thetotal frequency in each row is equal to k.Let C j be the number of times that an article is classified into the jth category.This is the column sum of frequencies which can be denoted by C j = ∑ ni=1 n ij.To find P(E), note that the proportion of articles assigned to the jth categoryis p j = C j /n • k. If the annotators make their assignments at random, theexpected proportion of agreement for each category would be p 2 j, and the totalexpected agreement across all categories can be computed by equation 4.257
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Chapter 1Introduction1.1 Motivation
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