Data Normalization

Data processing and normalization tasks evaluate structured output from messy prose and different structures. This capability is essential for catalogue and product pipelines where data needs to be extracted from unstructured text and formatted consistently. Models must understand the desired output format and extract relevant information accurately.

76
openai/gpt-5-mini
Average duration
21s
Average tokens
1752
Average cost
$0.00
0
19s
1862
opper_normalization_sample_01
50
23s
2629
opper_normalization_sample_02
100
16s
1647
opper_normalization_sample_03
0
19s
2166
opper_normalization_sample_04
50
19s
2137
opper_normalization_sample_05
50
31s
3543
opper_normalization_sample_06
100
17s
2402
opper_normalization_sample_07
50
26s
2898
opper_normalization_sample_08
50
35s
2928
opper_normalization_sample_09
100
23s
2090
opper_normalization_sample_10
100
14s
759
opper_normalization_sample_11
100
14s
1019
opper_normalization_sample_12
100
16s
1355
opper_normalization_sample_13
100
1m 11s
1647
opper_normalization_sample_14
100
14s
1329
opper_normalization_sample_15
100
14s
1005
opper_normalization_sample_16
50
10s
920
opper_normalization_sample_17
100
8s
848
opper_normalization_sample_18
50
14s
999
opper_normalization_sample_19
50
14s
2101
opper_normalization_sample_20
50
14s
1204
opper_normalization_sample_21
100
59s
1222
opper_normalization_sample_22
100
16s
1800
opper_normalization_sample_23
100
16s
1472
opper_normalization_sample_24
100
14s
1600
opper_normalization_sample_25
100
24s
2137
opper_normalization_sample_26
100
19s
1590
opper_normalization_sample_27