The contingency tables of the clustering results with three clusters are depicted in Table 5. Part A of the table depicts the solution obtained with theoretical features, while Part B represents the solution obtained with POS features. Rows are gold standard classes and columns are clusters, labeled with the cluster number provided by the algorithm. The ordering of the cluster numbers corresponds to the quality of the cluster, measured in terms of the clustering criterion (see Equation (2)), 0 representing the cluster with the highest quality. In each cell C_ij of Table 5, the number of adjectives of class i that are assigned to cluster j by the algorithm is given. The largest value for each class is highlighted (see gray cells).

Table 5 

First model: Three-way solution contingency tables for theoretical and POS features. Rows are gold standard classes, columns are clusters. Row Total_GS shows the number of Gold Standard lemmata and row Total_cl the total number of lemmata contained in each cluster. Note that the column labeled Total represents the row sum for each part (as the number of items per class is identical).

.	A: Theoretical .			B: POS .			.
Cluster .	0 .	1 .	2 .	0 .	1 .	2 .	Total .
intensional (I)	0	0		0		0	2
intensional-qualitative (IQ)	0	0		0		0	1
qualitative (Q)	4	13		10		5	52
qualitative-relational (QR)	3		3		2	2	11
relational (R)		13	1		5	10	35
TotalGS	28	31	42	37	47	17	101
Totalcl	834	1,287	1,400	1,234	1,754	533	3,521

.	A: Theoretical .			B: POS .			.
Cluster .	0 .	1 .	2 .	0 .	1 .	2 .	Total .
intensional (I)	0	0		0		0	2
intensional-qualitative (IQ)	0	0		0		0	1
qualitative (Q)	4	13		10		5	52
qualitative-relational (QR)	3		3		2	2	11
relational (R)		13	1		5	10	35
TotalGS	28	31	42	37	47	17	101
Totalcl	834	1,287	1,400	1,234	1,754	533	3,521

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