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.

74
openai/o4-mini
Average duration
22s
Average tokens
1688
Average cost
$0.00
0
19s
1654
opper_normalization_sample_01
100
21s
1944
opper_normalization_sample_02
100
21s
1909
opper_normalization_sample_03
0
19s
2050
opper_normalization_sample_04
50
12s
1498
opper_normalization_sample_05
50
20s
2217
opper_normalization_sample_06
0
20s
2304
opper_normalization_sample_07
50
42s
4271
opper_normalization_sample_08
50
37s
3952
opper_normalization_sample_09
100
37s
1636
opper_normalization_sample_10
100
21s
981
opper_normalization_sample_11
100
30s
1166
opper_normalization_sample_12
100
21s
1267
opper_normalization_sample_13
100
9s
1000
opper_normalization_sample_14
100
28s
1498
opper_normalization_sample_15
100
21s
1140
opper_normalization_sample_16
100
21s
1046
opper_normalization_sample_17
100
30s
1019
opper_normalization_sample_18
50
21s
886
opper_normalization_sample_19
50
20s
1965
opper_normalization_sample_20
50
20s
1114
opper_normalization_sample_21
100
21s
1114
opper_normalization_sample_22
100
19s
1533
opper_normalization_sample_23
100
19s
1531
opper_normalization_sample_24
100
20s
1477
opper_normalization_sample_25
50
19s
1719
opper_normalization_sample_26
100
20s
1682
opper_normalization_sample_27