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.

80
openai/o3-mini
Average duration
24s
Average tokens
1674
Average cost
$0.00
100
16s
1824
opper_normalization_sample_01
50
25s
2793
opper_normalization_sample_02
100
13s
1500
opper_normalization_sample_03
0
20s
2202
opper_normalization_sample_04
50
18s
2198
opper_normalization_sample_05
50
29s
3372
opper_normalization_sample_06
100
39s
1849
opper_normalization_sample_07
50
21s
2193
opper_normalization_sample_08
50
23s
2583
opper_normalization_sample_09
50
18s
1266
opper_normalization_sample_10
100
31s
947
opper_normalization_sample_11
100
13s
918
opper_normalization_sample_12
100
1m 4s
1434
opper_normalization_sample_13
100
27s
1394
opper_normalization_sample_14
100
29s
1650
opper_normalization_sample_15
100
13s
1187
opper_normalization_sample_16
100
8s
919
opper_normalization_sample_17
100
8s
862
opper_normalization_sample_18
50
13s
936
opper_normalization_sample_19
50
13s
2298
opper_normalization_sample_20
50
1m 41s
1047
opper_normalization_sample_21
100
16s
1527
opper_normalization_sample_22
100
13s
1670
opper_normalization_sample_23
100
13s
1441
opper_normalization_sample_24
100
11s
1494
opper_normalization_sample_25
100
18s
2021
opper_normalization_sample_26
100
31s
1661
opper_normalization_sample_27