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/gpt-4o
Average duration
19s
Average tokens
942
Average cost
$0.00
100
16s
944
opper_normalization_sample_01
100
17s
1153
opper_normalization_sample_02
100
17s
1185
opper_normalization_sample_03
0
1m 15s
922
opper_normalization_sample_04
50
17s
1207
opper_normalization_sample_05
50
17s
1134
opper_normalization_sample_06
0
16s
1405
opper_normalization_sample_07
50
17s
1337
opper_normalization_sample_08
50
17s
1669
opper_normalization_sample_09
50
16s
543
opper_normalization_sample_10
100
17s
447
opper_normalization_sample_11
100
17s
649
opper_normalization_sample_12
100
17s
743
opper_normalization_sample_13
100
16s
768
opper_normalization_sample_14
100
17s
910
opper_normalization_sample_15
100
17s
646
opper_normalization_sample_16
100
16s
630
opper_normalization_sample_17
100
16s
610
opper_normalization_sample_18
100
17s
614
opper_normalization_sample_19
50
16s
1587
opper_normalization_sample_20
50
16s
623
opper_normalization_sample_21
100
17s
774
opper_normalization_sample_22
100
17s
1004
opper_normalization_sample_23
100
17s
942
opper_normalization_sample_24
100
17s
919
opper_normalization_sample_25
100
17s
1051
opper_normalization_sample_26
100
17s
1030
opper_normalization_sample_27