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.

69
openai/gpt-4o-mini
Average duration
18s
Average tokens
893
Average cost
$0.00
100
16s
909
opper_normalization_sample_01
50
16s
1084
opper_normalization_sample_02
100
16s
1125
opper_normalization_sample_03
50
16s
876
opper_normalization_sample_04
50
16s
1136
opper_normalization_sample_05
50
16s
1086
opper_normalization_sample_06
100
16s
1280
opper_normalization_sample_07
50
18s
1289
opper_normalization_sample_08
50
18s
1589
opper_normalization_sample_09
50
16s
473
opper_normalization_sample_10
100
16s
424
opper_normalization_sample_11
0
16s
582
opper_normalization_sample_12
50
18s
735
opper_normalization_sample_13
100
18s
739
opper_normalization_sample_14
50
18s
888
opper_normalization_sample_15
100
15s
608
opper_normalization_sample_16
100
18s
595
opper_normalization_sample_17
50
18s
589
opper_normalization_sample_18
100
15s
603
opper_normalization_sample_19
100
18s
1462
opper_normalization_sample_20
0
48s
609
opper_normalization_sample_21
0
15s
651
opper_normalization_sample_22
100
18s
958
opper_normalization_sample_23
100
15s
906
opper_normalization_sample_24
100
15s
889
opper_normalization_sample_25
50
32s
1032
opper_normalization_sample_26
100
15s
1004
opper_normalization_sample_27