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Datasets:
amyrmahdy
/
decima-pii-testpack

Tasks:
Token Classification
Languages:
Arabic
Persian
Urdu
Size:
n<1K
Tags:
pii
pii-detection
test-set
arabic
persian
urdu
License:
Dataset card Data Studio Files
xet
 Community
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The full dataset viewer is not available (click to read why). Only showing a preview of the rows.
The dataset generation failed
Error code:   DatasetGenerationError
Exception:    CastError
Message:      Couldn't cast
all: struct<p: double, r: double, f1: double, gold: int64, pred: int64, tp: int64, untyped_f1: double, de (... 16 chars omitted)
  child 0, p: double
  child 1, r: double
  child 2, f1: double
  child 3, gold: int64
  child 4, pred: int64
  child 5, tp: int64
  child 6, untyped_f1: double
  child 7, detection: double
digits:arabic_indic: struct<p: double, r: double, f1: double, gold: int64, pred: int64, tp: int64, untyped_f1: double, de (... 16 chars omitted)
  child 0, p: double
  child 1, r: double
  child 2, f1: double
  child 3, gold: int64
  child 4, pred: int64
  child 5, tp: int64
  child 6, untyped_f1: double
  child 7, detection: double
digits:ascii: struct<p: double, r: double, f1: double, gold: int64, pred: int64, tp: int64, untyped_f1: double, de (... 16 chars omitted)
  child 0, p: double
  child 1, r: double
  child 2, f1: double
  child 3, gold: int64
  child 4, pred: int64
  child 5, tp: int64
  child 6, untyped_f1: double
  child 7, detection: double
digits:mixed: struct<p: double, r: double, f1: double, gold: int64, pred: int64, tp: int64, untyped_f1: double, de (... 16 chars omitted)
  child 0, p: double
  child 1, r: double
  child 2, f1: double
  child 3, gold: int64
  child 4, pred: int64
  child 5, tp: int64
  child 6, untyped_f1: double
  child 7, detection: double
digits:none: struct<p: double, r: double, f1: double, gold: int64, pred: int64, tp: int64, untyped_f1: double, de (... 16 chars omitted)
  child 0, p: double
  child 1, r: double
  child 2, 
...
, touched: int64
      child 1, total: int64
      child 2, rate: double
  child 15, org: struct<touched: int64, total: int64, rate: double>
      child 0, touched: int64
      child 1, total: int64
      child 2, rate: double
  child 16, sku: struct<touched: int64, total: int64, rate: double>
      child 0, touched: int64
      child 1, total: int64
      child 2, rate: double
  child 17, ticket: struct<touched: int64, total: int64, rate: double>
      child 0, touched: int64
      child 1, total: int64
      child 2, rate: double
  child 18, tracking: struct<touched: int64, total: int64, rate: double>
      child 0, touched: int64
      child 1, total: int64
      child 2, rate: double
  child 19, ts: struct<touched: int64, total: int64, rate: double>
      child 0, touched: int64
      child 1, total: int64
      child 2, rate: double
  child 20, version: struct<touched: int64, total: int64, rate: double>
      child 0, touched: int64
      child 1, total: int64
      child 2, rate: double
  child 21, wats: struct<touched: int64, total: int64, rate: double>
      child 0, touched: int64
      child 1, total: int64
      child 2, rate: double
pii_free_rows_with_prediction: struct<rows: int64, rate: double>
  child 0, rows: int64
  child 1, rate: double
spans: list<item: struct<start: int64, end: int64, label: string>>
  child 0, item: struct<start: int64, end: int64, label: string>
      child 0, start: int64
      child 1, end: int64
      child 2, label: string
id: string
to
{'id': Value('string'), 'spans': List({'start': Value('int64'), 'end': Value('int64'), 'label': Value('string')})}
because column names don't match
Traceback:    Traceback (most recent call last):
                File "/usr/local/lib/python3.14/site-packages/datasets/builder.py", line 1835, in _prepare_split_single
                  for key, table in generator:
                                    ^^^^^^^^^
                File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 621, in wrapped
                  for item in generator(*args, **kwargs):
                              ~~~~~~~~~^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/json/json.py", line 361, in _generate_tables
                  self._cast_table(pa_table, json_field_paths=json_field_paths),
                  ~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/json/json.py", line 132, in _cast_table
                  pa_table = table_cast(pa_table, self.info.features.arrow_schema)
                File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2381, in table_cast
                  return cast_table_to_schema(table, schema)
                File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2309, in cast_table_to_schema
                  raise CastError(
                  ...<3 lines>...
                  )
              datasets.table.CastError: Couldn't cast
              all: struct<p: double, r: double, f1: double, gold: int64, pred: int64, tp: int64, untyped_f1: double, de (... 16 chars omitted)
                child 0, p: double
                child 1, r: double
                child 2, f1: double
                child 3, gold: int64
                child 4, pred: int64
                child 5, tp: int64
                child 6, untyped_f1: double
                child 7, detection: double
              digits:arabic_indic: struct<p: double, r: double, f1: double, gold: int64, pred: int64, tp: int64, untyped_f1: double, de (... 16 chars omitted)
                child 0, p: double
                child 1, r: double
                child 2, f1: double
                child 3, gold: int64
                child 4, pred: int64
                child 5, tp: int64
                child 6, untyped_f1: double
                child 7, detection: double
              digits:ascii: struct<p: double, r: double, f1: double, gold: int64, pred: int64, tp: int64, untyped_f1: double, de (... 16 chars omitted)
                child 0, p: double
                child 1, r: double
                child 2, f1: double
                child 3, gold: int64
                child 4, pred: int64
                child 5, tp: int64
                child 6, untyped_f1: double
                child 7, detection: double
              digits:mixed: struct<p: double, r: double, f1: double, gold: int64, pred: int64, tp: int64, untyped_f1: double, de (... 16 chars omitted)
                child 0, p: double
                child 1, r: double
                child 2, f1: double
                child 3, gold: int64
                child 4, pred: int64
                child 5, tp: int64
                child 6, untyped_f1: double
                child 7, detection: double
              digits:none: struct<p: double, r: double, f1: double, gold: int64, pred: int64, tp: int64, untyped_f1: double, de (... 16 chars omitted)
                child 0, p: double
                child 1, r: double
                child 2, 
              ...
              , touched: int64
                    child 1, total: int64
                    child 2, rate: double
                child 15, org: struct<touched: int64, total: int64, rate: double>
                    child 0, touched: int64
                    child 1, total: int64
                    child 2, rate: double
                child 16, sku: struct<touched: int64, total: int64, rate: double>
                    child 0, touched: int64
                    child 1, total: int64
                    child 2, rate: double
                child 17, ticket: struct<touched: int64, total: int64, rate: double>
                    child 0, touched: int64
                    child 1, total: int64
                    child 2, rate: double
                child 18, tracking: struct<touched: int64, total: int64, rate: double>
                    child 0, touched: int64
                    child 1, total: int64
                    child 2, rate: double
                child 19, ts: struct<touched: int64, total: int64, rate: double>
                    child 0, touched: int64
                    child 1, total: int64
                    child 2, rate: double
                child 20, version: struct<touched: int64, total: int64, rate: double>
                    child 0, touched: int64
                    child 1, total: int64
                    child 2, rate: double
                child 21, wats: struct<touched: int64, total: int64, rate: double>
                    child 0, touched: int64
                    child 1, total: int64
                    child 2, rate: double
              pii_free_rows_with_prediction: struct<rows: int64, rate: double>
                child 0, rows: int64
                child 1, rate: double
              spans: list<item: struct<start: int64, end: int64, label: string>>
                child 0, item: struct<start: int64, end: int64, label: string>
                    child 0, start: int64
                    child 1, end: int64
                    child 2, label: string
              id: string
              to
              {'id': Value('string'), 'spans': List({'start': Value('int64'), 'end': Value('int64'), 'label': Value('string')})}
              because column names don't match
              
              The above exception was the direct cause of the following exception:
              
              Traceback (most recent call last):
                File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 1379, in compute_config_parquet_and_info_response
                  parquet_operations, partial, estimated_dataset_info = stream_convert_to_parquet(
                                                                        ~~~~~~~~~~~~~~~~~~~~~~~~~^
                      builder, max_dataset_size_bytes=max_dataset_size_bytes
                      ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                  )
                  ^
                File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 956, in stream_convert_to_parquet
                  builder._prepare_split(split_generator=splits_generators[split], file_format="parquet")
                  ~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/builder.py", line 1702, in _prepare_split
                  for job_id, done, content in self._prepare_split_single(
                                               ~~~~~~~~~~~~~~~~~~~~~~~~~~^
                      gen_kwargs=gen_kwargs, job_id=job_id, **_prepare_split_args
                      ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                  ):
                  ^
                File "/usr/local/lib/python3.14/site-packages/datasets/builder.py", line 1887, in _prepare_split_single
                  raise DatasetGenerationError("An error occurred while generating the dataset") from e
              datasets.exceptions.DatasetGenerationError: An error occurred while generating the dataset

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id
string
spans
list
16270afab43d
[ { "start": 26, "end": 41, "label": "PERSON_NAME" }, { "start": 48, "end": 58, "label": "PERSON_NAME" }, { "start": 67, "end": 77, "label": "DATE_OF_BIRTH" } ]
a2409d8a5a5b
[ { "start": 55, "end": 73, "label": "NATIONAL_ID" }, { "start": 116, "end": 151, "label": "ADDRESS" }, { "start": 163, "end": 179, "label": "PERSON_NAME" } ]
0167b130ee77
[]
cf1a97860077
[ { "start": 52, "end": 69, "label": "CARD" }, { "start": 99, "end": 111, "label": "PERSON_NAME" } ]
08638d5528a2
[]
3afd130cd31b
[ { "start": 65, "end": 71, "label": "NATIONAL_ID" }, { "start": 81, "end": 91, "label": "PERSON_NAME" }, { "start": 139, "end": 157, "label": "EMAIL" }, { "start": 161, "end": 191, "label": "IP_ADDRESS" }, { "start": 257, "end": 264, "label"...
c0600da0c096
[ { "start": 19, "end": 29, "label": "NATIONAL_ID" }, { "start": 35, "end": 51, "label": "PERSON_NAME" } ]
945ea212db9d
[ { "start": 16, "end": 24, "label": "PASSPORT" }, { "start": 34, "end": 53, "label": "CARD" }, { "start": 101, "end": 121, "label": "EMAIL" }, { "start": 138, "end": 170, "label": "ADDRESS" } ]
d32badbb3497
[ { "start": 17, "end": 23, "label": "PERSON_NAME" }, { "start": 38, "end": 74, "label": "IBAN" }, { "start": 125, "end": 129, "label": "PERSON_NAME" }, { "start": 202, "end": 209, "label": "PERSON_NAME" }, { "start": 230, "end": 240, "label"...
7cd1e2972edb
[]
7ac6885ac9d9
[ { "start": 65, "end": 76, "label": "NATIONAL_ID" }, { "start": 86, "end": 103, "label": "PERSON_NAME" }, { "start": 170, "end": 188, "label": "NATIONAL_ID" }, { "start": 198, "end": 210, "label": "PERSON_NAME" }, { "start": 259, "end": 279, ...
4b54099e8d69
[ { "start": 24, "end": 42, "label": "NATIONAL_ID" }, { "start": 72, "end": 81, "label": "PERSON_NAME" }, { "start": 91, "end": 102, "label": "PERSON_NAME" } ]
47478d5cd874
[ { "start": 16, "end": 20, "label": "PERSON_NAME" }, { "start": 26, "end": 39, "label": "PERSON_NAME" }, { "start": 46, "end": 60, "label": "PHONE" }, { "start": 92, "end": 96, "label": "PERSON_NAME" }, { "start": 124, "end": 152, "label": "...
44b0c3b98be1
[ { "start": 44, "end": 64, "label": "EMAIL" }, { "start": 88, "end": 98, "label": "NATIONAL_ID" }, { "start": 125, "end": 133, "label": "PERSON_NAME" } ]
a02370d77b84
[ { "start": 48, "end": 57, "label": "PASSPORT" } ]
9dc22e328d0e
[ { "start": 21, "end": 31, "label": "DATE_OF_BIRTH" } ]
49fd01ee46f6
[ { "start": 19, "end": 29, "label": "DATE_OF_BIRTH" }, { "start": 45, "end": 59, "label": "IP_ADDRESS" }, { "start": 74, "end": 93, "label": "CARD" }, { "start": 115, "end": 123, "label": "PASSPORT" } ]
a9b85ca07fde
[]
ad187fee1ae2
[ { "start": 26, "end": 39, "label": "PERSON_NAME" }, { "start": 69, "end": 99, "label": "IBAN" }, { "start": 106, "end": 120, "label": "PERSON_NAME" } ]
5985d2cbabd2
[ { "start": 46, "end": 70, "label": "EMAIL" }, { "start": 74, "end": 88, "label": "IP_ADDRESS" }, { "start": 135, "end": 159, "label": "EMAIL" }, { "start": 163, "end": 177, "label": "IP_ADDRESS" }, { "start": 243, "end": 257, "label": "NATI...
698ec3a97afb
[ { "start": 24, "end": 42, "label": "NATIONAL_ID" } ]
d4a9426fbeb9
[ { "start": 38, "end": 74, "label": "IBAN" }, { "start": 104, "end": 108, "label": "PERSON_NAME" } ]
0d8ba0005ee9
[]
6749115a6c23
[ { "start": 24, "end": 37, "label": "PERSON_NAME" }, { "start": 48, "end": 61, "label": "PHONE" } ]
b04f82063999
[ { "start": 17, "end": 51, "label": "ADDRESS" }, { "start": 65, "end": 80, "label": "PHONE" }, { "start": 96, "end": 111, "label": "PERSON_NAME" } ]
5758d0b68217
[ { "start": 20, "end": 38, "label": "NATIONAL_ID" } ]
c3e254ce8a31
[ { "start": 13, "end": 29, "label": "CARD" } ]
e19ab64e5dc3
[ { "start": 46, "end": 66, "label": "EMAIL" }, { "start": 70, "end": 84, "label": "IP_ADDRESS" }, { "start": 150, "end": 168, "label": "NATIONAL_ID" }, { "start": 178, "end": 192, "label": "PERSON_NAME" }, { "start": 240, "end": 259, "label"...
336110592980
[]
1e1df678443a
[ { "start": 38, "end": 50, "label": "IP_ADDRESS" }, { "start": 71, "end": 80, "label": "PERSON_NAME" } ]
2d2e82b9ef8b
[ { "start": 6, "end": 22, "label": "CARD" } ]
a44e71f4566a
[ { "start": 17, "end": 49, "label": "ADDRESS" }, { "start": 68, "end": 76, "label": "PASSPORT" } ]
8cb807bf05b4
[ { "start": 46, "end": 84, "label": "ADDRESS" } ]
f1ae23f73327
[ { "start": 17, "end": 46, "label": "IBAN" } ]
0c00a9c464f5
[ { "start": 17, "end": 21, "label": "PERSON_NAME" }, { "start": 50, "end": 69, "label": "CARD" }, { "start": 128, "end": 158, "label": "IBAN" }, { "start": 189, "end": 193, "label": "PERSON_NAME" }, { "start": 222, "end": 232, "label": "PHON...
ebe1fd45a40d
[ { "start": 45, "end": 64, "label": "EMAIL" }, { "start": 68, "end": 82, "label": "IP_ADDRESS" }, { "start": 129, "end": 154, "label": "EMAIL" }, { "start": 158, "end": 172, "label": "IP_ADDRESS" } ]
d5c221b61c0a
[]
4403b4f7adcb
[ { "start": 65, "end": 77, "label": "NATIONAL_ID" }, { "start": 87, "end": 98, "label": "PERSON_NAME" }, { "start": 165, "end": 177, "label": "NATIONAL_ID" }, { "start": 187, "end": 199, "label": "PERSON_NAME" }, { "start": 266, "end": 276, ...
ce23436d1a4a
[]
a365370abe58
[ { "start": 60, "end": 95, "label": "ADDRESS" } ]
4d8414003582
[ { "start": 17, "end": 20, "label": "PERSON_NAME" }, { "start": 32, "end": 48, "label": "PHONE" }, { "start": 75, "end": 78, "label": "PERSON_NAME" }, { "start": 103, "end": 117, "label": "NATIONAL_ID" }, { "start": 123, "end": 139, "label":...
77025d040f00
[]
dfd6d0a2648b
[ { "start": 18, "end": 23, "label": "PERSON_NAME" }, { "start": 40, "end": 88, "label": "ADDRESS" }, { "start": 129, "end": 138, "label": "PASSPORT" }, { "start": 168, "end": 173, "label": "PERSON_NAME" }, { "start": 202, "end": 212, "label"...
9a173181a9e2
[ { "start": 29, "end": 46, "label": "PERSON_NAME" }, { "start": 71, "end": 90, "label": "CARD" } ]
c09c34f95152
[ { "start": 25, "end": 34, "label": "PERSON_NAME" }, { "start": 62, "end": 76, "label": "NATIONAL_ID" }, { "start": 88, "end": 106, "label": "EMAIL" } ]
a578b83fdcbe
[ { "start": 64, "end": 72, "label": "NATIONAL_ID" }, { "start": 82, "end": 95, "label": "PERSON_NAME" }, { "start": 162, "end": 169, "label": "NATIONAL_ID" }, { "start": 179, "end": 196, "label": "PERSON_NAME" }, { "start": 263, "end": 281, ...
cf6933158432
[ { "start": 20, "end": 34, "label": "NATIONAL_ID" } ]
1e98759432d8
[ { "start": 17, "end": 24, "label": "PERSON_NAME" }, { "start": 45, "end": 55, "label": "NATIONAL_ID" }, { "start": 61, "end": 76, "label": "PERSON_NAME" } ]
3d43627e1d8d
[]
51959ed8fc1d
[]
dfb625051b90
[ { "start": 31, "end": 39, "label": "PASSPORT" }, { "start": 106, "end": 109, "label": "PERSON_NAME" } ]
a208db30cd9a
[ { "start": 23, "end": 33, "label": "DATE_OF_BIRTH" }, { "start": 67, "end": 81, "label": "PERSON_NAME" } ]
44848d603a90
[ { "start": 13, "end": 37, "label": "IBAN" } ]
ab7d1cb7236f
[ { "start": 45, "end": 55, "label": "DATE_OF_BIRTH" }, { "start": 67, "end": 71, "label": "PERSON_NAME" } ]
eb946c90135b
[ { "start": 19, "end": 22, "label": "PERSON_NAME" }, { "start": 47, "end": 61, "label": "NATIONAL_ID" }, { "start": 67, "end": 77, "label": "PERSON_NAME" } ]
a80938daf8b0
[ { "start": 45, "end": 62, "label": "EMAIL" }, { "start": 66, "end": 78, "label": "IP_ADDRESS" }, { "start": 143, "end": 161, "label": "NATIONAL_ID" }, { "start": 171, "end": 182, "label": "PERSON_NAME" }, { "start": 231, "end": 253, "label"...
0727fe3e6316
[ { "start": 32, "end": 42, "label": "PERSON_NAME" }, { "start": 73, "end": 91, "label": "NATIONAL_ID" } ]
9bd5add362d5
[]
35abf65e3da8
[ { "start": 65, "end": 75, "label": "NATIONAL_ID" }, { "start": 85, "end": 96, "label": "PERSON_NAME" }, { "start": 163, "end": 178, "label": "NATIONAL_ID" }, { "start": 188, "end": 203, "label": "PERSON_NAME" }, { "start": 270, "end": 285, ...
99c1f860ff5d
[ { "start": 26, "end": 63, "label": "IBAN" } ]
bac57129f2cb
[ { "start": 0, "end": 4, "label": "PERSON_NAME" }, { "start": 60, "end": 78, "label": "NATIONAL_ID" } ]
5b7ef835ccee
[ { "start": 6, "end": 14, "label": "PASSPORT" } ]
1361c92cac2c
[ { "start": 24, "end": 37, "label": "PHONE" } ]
7ce516c1f1c7
[]
79668d885ddd
[ { "start": 50, "end": 60, "label": "PHONE" }, { "start": 115, "end": 133, "label": "NATIONAL_ID" } ]
a092eeaa84fa
[ { "start": 24, "end": 37, "label": "PHONE" } ]
4484391bdaf4
[ { "start": 17, "end": 21, "label": "PERSON_NAME" }, { "start": 29, "end": 40, "label": "PERSON_NAME" }, { "start": 49, "end": 59, "label": "DATE_OF_BIRTH" } ]
824453d9072d
[ { "start": 15, "end": 25, "label": "DATE_OF_BIRTH" }, { "start": 40, "end": 50, "label": "PERSON_NAME" }, { "start": 60, "end": 82, "label": "EMAIL" } ]
fd28d0edde62
[ { "start": 34, "end": 46, "label": "NATIONAL_ID" } ]
9924692c0480
[]
487e8f148a8e
[ { "start": 17, "end": 20, "label": "PERSON_NAME" }, { "start": 61, "end": 90, "label": "IBAN" }, { "start": 108, "end": 117, "label": "PERSON_NAME" }, { "start": 158, "end": 194, "label": "IBAN" }, { "start": 212, "end": 216, "label": "PERS...
a103e16a7414
[]
4d6a3de1b273
[ { "start": 46, "end": 64, "label": "EMAIL" }, { "start": 68, "end": 83, "label": "IP_ADDRESS" } ]
359df0e8bd52
[]
86a942b11578
[ { "start": 91, "end": 122, "label": "EMAIL" }, { "start": 139, "end": 143, "label": "PERSON_NAME" } ]
0dadc80122f0
[ { "start": 51, "end": 60, "label": "PASSPORT" }, { "start": 85, "end": 88, "label": "PERSON_NAME" } ]
252af2d0c845
[ { "start": 73, "end": 83, "label": "NATIONAL_ID" }, { "start": 95, "end": 99, "label": "PERSON_NAME" } ]
f7696d75074d
[]
471a6425418d
[ { "start": 46, "end": 69, "label": "EMAIL" }, { "start": 73, "end": 85, "label": "IP_ADDRESS" }, { "start": 151, "end": 169, "label": "NATIONAL_ID" }, { "start": 179, "end": 189, "label": "PERSON_NAME" }, { "start": 237, "end": 263, "label"...
2bc648c9c219
[ { "start": 48, "end": 62, "label": "NATIONAL_ID" }, { "start": 68, "end": 79, "label": "PERSON_NAME" }, { "start": 92, "end": 96, "label": "PERSON_NAME" } ]
3c0630d94872
[ { "start": 43, "end": 64, "label": "EMAIL" }, { "start": 81, "end": 85, "label": "PERSON_NAME" } ]
eab2356ca609
[ { "start": 29, "end": 41, "label": "PERSON_NAME" }, { "start": 100, "end": 116, "label": "CARD" } ]
981cdfa5c8f2
[ { "start": 4, "end": 12, "label": "PERSON_NAME" }, { "start": 18, "end": 31, "label": "PHONE" }, { "start": 64, "end": 74, "label": "NATIONAL_ID" } ]
fa5772401d91
[ { "start": 16, "end": 25, "label": "PASSPORT" } ]
ab7c972800aa
[ { "start": 64, "end": 74, "label": "NATIONAL_ID" }, { "start": 84, "end": 99, "label": "PERSON_NAME" } ]
ecc875f89f54
[ { "start": 72, "end": 120, "label": "ADDRESS" } ]
c602ddf71907
[ { "start": 64, "end": 75, "label": "NATIONAL_ID" }, { "start": 85, "end": 93, "label": "PERSON_NAME" }, { "start": 142, "end": 159, "label": "EMAIL" }, { "start": 163, "end": 177, "label": "IP_ADDRESS" }, { "start": 223, "end": 241, "label"...
16aa92f5ed10
[ { "start": 17, "end": 20, "label": "PERSON_NAME" }, { "start": 39, "end": 75, "label": "IBAN" }, { "start": 126, "end": 155, "label": "IBAN" } ]
8dfa99d1db4c
[ { "start": 29, "end": 44, "label": "PERSON_NAME" }, { "start": 54, "end": 64, "label": "PHONE" } ]
b55e7f66791a
[ { "start": 51, "end": 63, "label": "NATIONAL_ID" }, { "start": 69, "end": 84, "label": "PERSON_NAME" } ]
ece9ba6e21f1
[ { "start": 23, "end": 37, "label": "NATIONAL_ID" }, { "start": 43, "end": 60, "label": "PERSON_NAME" }, { "start": 95, "end": 120, "label": "EMAIL" } ]
7458f600845e
[]
f90a26fb8d49
[ { "start": 6, "end": 35, "label": "IBAN" } ]
0b2cbd63c79e
[ { "start": 4, "end": 15, "label": "PERSON_NAME" }, { "start": 21, "end": 33, "label": "PHONE" } ]
e063def36946
[ { "start": 64, "end": 79, "label": "NATIONAL_ID" }, { "start": 89, "end": 102, "label": "PERSON_NAME" }, { "start": 151, "end": 180, "label": "EMAIL" }, { "start": 184, "end": 195, "label": "IP_ADDRESS" } ]
617dd84cd521
[ { "start": 17, "end": 21, "label": "PERSON_NAME" }, { "start": 30, "end": 39, "label": "PERSON_NAME" }, { "start": 60, "end": 81, "label": "EMAIL" }, { "start": 109, "end": 113, "label": "PERSON_NAME" }, { "start": 121, "end": 135, "label":...
842bf7e92fe9
[ { "start": 45, "end": 62, "label": "EMAIL" }, { "start": 66, "end": 81, "label": "IP_ADDRESS" } ]
3474b4046861
[ { "start": 17, "end": 47, "label": "IBAN" } ]
7e3f9d1c2830
[ { "start": 15, "end": 29, "label": "DATE_OF_BIRTH" }, { "start": 35, "end": 46, "label": "IP_ADDRESS" }, { "start": 64, "end": 73, "label": "PASSPORT" } ]
264320637cc4
[ { "start": 27, "end": 46, "label": "CARD" } ]
End of preview.

decima-pii test pack

500 labelled messages (100 each in Arabic, Persian, Urdu, Turkish and English) for checking that an integration of decima-pii reproduces the reference output. All text and values are synthetic: the names, phone numbers, IDs, IBANs and card numbers are generated in their real formats and belong to no one. The rows are a fixed random sample (seed 2026) of decima-pii's own held-out test set.

This is a reproduction check, not an accuracy claim: the model was tuned with this test set's error categories in mind, so scores here are near-perfect. For accuracy on text the model never saw, see the outside results on the model card.

Files

file what sha256
testpack.jsonl {id, lang, variety, digits_script, text, spans: [{start, end, label}], negatives} (character offsets; negatives are look-alike values that are not personal data) c31cd4e32538315c15b5ed8e9f18c9a4a1a20e4f2fc2244a8719320961f0afea
expected-decima-pii-v0.1-nbits8.jsonl the reference output {id, spans} of decima-pii v0.1, onnx/model_nbits8.onnx, run through decima_pii.py (bridging, post-filter, windowing) 9fc789c42e1c31b264a76380a38c1b90b4d1bf0538a8d7fc266ba74f9d521b4a
metrics-decima-pii-v0.1-nbits8.json the scores below, per language and per label

Pinned model

amyrmahdy/decima-pii at tag v0.1 (commit a90c86f8f426d61895866024370fd96e30d37f4b):

file sha256
onnx/model_nbits8.onnx (default) 473e6150c2f6bd9fe47a3164cf64c3dedccc1ec5697828c335c028f72ce98bf3
onnx/model_quantized.onnx (browser) 297109796d3880daa553f107eb727804ae4235ccc9d68b305c1471ceb15d4c24
onnx/model.onnx (fp32) 6b49793bd411c6937de9b5a6efc8c9d60eda08c22b96e66245870fac36eee8cd
tokenizer.json 4379fe7f4a7af10b1ac15ffc8ae90f446f92082393699e9dd54b8c3b5ec0abad

Reference scores (exact span and label)

precision recall F1
all (1,124 spans) 0.993 0.999 0.996
Arabic 0.991 1.000 0.996
Persian 0.974 0.996 0.984
Urdu 1.000 1.000 1.000
Turkish 1.000 1.000 1.000
English 1.000 1.000 1.000

An integration reproduces decima-pii when its spans equal expected-decima-pii-v0.1-nbits8.jsonl row for row (same offsets and labels). Note that the tokenizer file carries a 256-token truncation setting: disable it and tag long texts in overlapping windows, as decima_pii.py does.
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