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The dataset generation failed
Error code:   DatasetGenerationError
Exception:    CastError
Message:      Couldn't cast
split: string
item: struct<item_id: string, cik: int64, form: string, filed: timestamp[s], period_end: timestamp[s], fis (... 982 chars omitted)
  child 0, item_id: string
  child 1, cik: int64
  child 2, form: string
  child 3, filed: timestamp[s]
  child 4, period_end: timestamp[s]
  child 5, fiscal_period: string
  child 6, text: string
  child 7, truth: struct<period_end: timestamp[s], fiscal_period: string, revenue: double, cost_of_revenue: double, op (... 269 chars omitted)
      child 0, period_end: timestamp[s]
      child 1, fiscal_period: string
      child 2, revenue: double
      child 3, cost_of_revenue: double
      child 4, operating_income: double
      child 5, net_income: double
      child 6, eps_basic: double
      child 7, eps_diluted: double
      child 8, shares_diluted: double
      child 9, total_assets: double
      child 10, total_liabilities: double
      child 11, cash_and_equivalents: double
      child 12, stockholders_equity: double
      child 13, auditor_name: string
      child 14, state_of_incorporation: string
  child 8, context: struct<scale: double, share_scale: double, distractors: struct<revenue: list<item: double>, operatin (... 427 chars omitted)
      child 0, scale: double
      child 1, share_scale: double
      child 2, distractors: struct<revenue: list<item: double>, operating_income: list<item: double>, net_income: list<item: dou (... 370 chars omitted)
          child 0, revenue: list<item: double>
              child 0, item: double
          child 1, operating_income: list<item: double>
              child 0, item: double
          child 2, net_income: list<item: double>
              child 0, item: double
          child 3, eps_basic: list<item: double>
              child 0, item: double
          child 4, eps_diluted: list<item: double>
              child 0, item: double
          child 5, shares_diluted: list<item: double>
              child 0, item: double
          child 6, total_assets: list<item: double>
              child 0, item: double
          child 7, total_liabilities: list<item: double>
              child 0, item: double
          child 8, cash_and_equivalents: list<item: double>
              child 0, item: double
          child 9, stockholders_equity: list<item: double>
              child 0, item: double
          child 10, cost_of_revenue: list<item: double>
              child 0, item: double
          child 11, period_end: list<item: timestamp[s]>
              child 0, item: timestamp[s]
          child 12, auditor_name: list<item: string>
              child 0, item: string
  child 9, not_on_page: list<item: string>
      child 0, item: string
field: string
item_id: string
reason: string
to
{'item_id': Value('string'), 'reason': Value('string'), 'field': 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 1827, in _prepare_split_single
                  for key, table in generator:
                                    ^^^^^^^^^
                File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 613, in wrapped
                  for item in generator(*args, **kwargs):
                              ~~~~~~~~~^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/json/json.py", line 343, 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 2378, in table_cast
                  return cast_table_to_schema(table, schema)
                File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2306, in cast_table_to_schema
                  raise CastError(
                  ...<3 lines>...
                  )
              datasets.table.CastError: Couldn't cast
              split: string
              item: struct<item_id: string, cik: int64, form: string, filed: timestamp[s], period_end: timestamp[s], fis (... 982 chars omitted)
                child 0, item_id: string
                child 1, cik: int64
                child 2, form: string
                child 3, filed: timestamp[s]
                child 4, period_end: timestamp[s]
                child 5, fiscal_period: string
                child 6, text: string
                child 7, truth: struct<period_end: timestamp[s], fiscal_period: string, revenue: double, cost_of_revenue: double, op (... 269 chars omitted)
                    child 0, period_end: timestamp[s]
                    child 1, fiscal_period: string
                    child 2, revenue: double
                    child 3, cost_of_revenue: double
                    child 4, operating_income: double
                    child 5, net_income: double
                    child 6, eps_basic: double
                    child 7, eps_diluted: double
                    child 8, shares_diluted: double
                    child 9, total_assets: double
                    child 10, total_liabilities: double
                    child 11, cash_and_equivalents: double
                    child 12, stockholders_equity: double
                    child 13, auditor_name: string
                    child 14, state_of_incorporation: string
                child 8, context: struct<scale: double, share_scale: double, distractors: struct<revenue: list<item: double>, operatin (... 427 chars omitted)
                    child 0, scale: double
                    child 1, share_scale: double
                    child 2, distractors: struct<revenue: list<item: double>, operating_income: list<item: double>, net_income: list<item: dou (... 370 chars omitted)
                        child 0, revenue: list<item: double>
                            child 0, item: double
                        child 1, operating_income: list<item: double>
                            child 0, item: double
                        child 2, net_income: list<item: double>
                            child 0, item: double
                        child 3, eps_basic: list<item: double>
                            child 0, item: double
                        child 4, eps_diluted: list<item: double>
                            child 0, item: double
                        child 5, shares_diluted: list<item: double>
                            child 0, item: double
                        child 6, total_assets: list<item: double>
                            child 0, item: double
                        child 7, total_liabilities: list<item: double>
                            child 0, item: double
                        child 8, cash_and_equivalents: list<item: double>
                            child 0, item: double
                        child 9, stockholders_equity: list<item: double>
                            child 0, item: double
                        child 10, cost_of_revenue: list<item: double>
                            child 0, item: double
                        child 11, period_end: list<item: timestamp[s]>
                            child 0, item: timestamp[s]
                        child 12, auditor_name: list<item: string>
                            child 0, item: string
                child 9, not_on_page: list<item: string>
                    child 0, item: string
              field: string
              item_id: string
              reason: string
              to
              {'item_id': Value('string'), 'reason': Value('string'), 'field': 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 1369, 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 948, 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 1694, 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 1879, 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

Need help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.

item_id
string
reason
string
field
string
0000002969-22-000010
unlocatable
period_end
0000002969-22-000026
unlocatable
period_end
0000002969-22-000038
unlocatable
period_end
0000002969-22-000054
unlocatable
period_end
0000002969-23-000014
unlocatable
period_end
0000002969-23-000023
unlocatable
period_end
0000002969-23-000037
unlocatable
period_end
0000002969-23-000047
unlocatable
period_end
0000002969-24-000010
unlocatable
period_end
0000002969-24-000026
unlocatable
period_end
0000002969-24-000043
unlocatable
period_end
0000002969-24-000056
unlocatable
period_end
0000002969-25-000013
unlocatable
period_end
0000002969-25-000027
unlocatable
period_end
0000002969-25-000044
unlocatable
period_end
0000002969-25-000055
unlocatable
period_end
0000002969-26-000008
unlocatable
period_end
0000002969-26-000020
unlocatable
period_end
0000004962-22-000008
unlocatable
revenue
0000004962-22-000028
unlocatable
revenue
0000004962-22-000041
unlocatable
revenue
0000004962-22-000054
unlocatable
revenue
0000004962-23-000006
unlocatable
revenue
0000004962-23-000016
unlocatable
revenue
0000004962-23-000028
unlocatable
revenue
0000004962-23-000038
unlocatable
revenue
0000004962-24-000013
unlocatable
revenue
0000004962-24-000031
unlocatable
revenue
0000004962-24-000052
unlocatable
revenue
0000004962-24-000068
unlocatable
revenue
0000004962-25-000016
unlocatable
revenue
0000004962-25-000045
unlocatable
revenue
0000004962-25-000083
unlocatable
revenue
0000004962-25-000222
unlocatable
revenue
0000004962-26-000080
unlocatable
revenue
0000004962-26-000192
unlocatable
revenue
0000006201-22-000026
truth_missing
revenue
0000006201-22-000046
truth_missing
revenue
0000006201-22-000071
truth_missing
revenue
0000006201-22-000086
truth_missing
revenue
0000006201-23-000018
truth_missing
revenue
0000006201-23-000042
truth_missing
revenue
0000006201-23-000070
truth_missing
revenue
0000006201-23-000092
truth_missing
revenue
0000006201-24-000010
truth_missing
revenue
0000006201-24-000032
truth_missing
revenue
0000006201-24-000048
truth_missing
revenue
0000006201-24-000060
truth_missing
revenue
0000006201-25-000010
truth_missing
revenue
0000006201-25-000023
truth_missing
revenue
0000006201-25-000038
truth_missing
revenue
0000006201-25-000052
truth_missing
revenue
0000006201-26-000014
truth_missing
revenue
0000006201-26-000032
truth_missing
revenue
0000008818-22-000009
no_balance_sheet
null
0000008818-22-000012
no_balance_sheet
null
0000008818-22-000014
unlocatable
total_assets
0000008818-23-000002
unlocatable
total_assets
0000008818-23-000009
no_balance_sheet
null
0000008818-23-000015
no_balance_sheet
null
0000008818-23-000018
no_balance_sheet
null
0000008818-24-000003
no_balance_sheet
null
0000008818-24-000009
no_balance_sheet
null
0000008818-24-000015
no_balance_sheet
null
0000008818-24-000017
no_balance_sheet
null
0000012208-22-000011
unlocatable
total_liabilities
0000012208-22-000026
unlocatable
total_liabilities
0000012208-22-000046
unlocatable
total_liabilities
0000012208-22-000071
unlocatable
total_liabilities
0000012208-23-000031
unlocatable
total_liabilities
0000012208-23-000047
unlocatable
total_liabilities
0000012208-23-000063
unlocatable
total_liabilities
0000012208-23-000072
unlocatable
total_liabilities
0000012208-24-000013
unlocatable
total_liabilities
0000012208-24-000039
unlocatable
total_liabilities
0000012208-24-000052
unlocatable
total_liabilities
0000012208-24-000063
unlocatable
total_liabilities
0000012208-25-000007
unlocatable
total_liabilities
0000012208-25-000026
unlocatable
total_liabilities
0000012208-25-000052
unlocatable
total_liabilities
0000012208-25-000077
unlocatable
total_liabilities
0000012208-26-000010
unlocatable
total_liabilities
0000012208-26-000035
unlocatable
total_liabilities
0000014707-22-000019
unlocatable
revenue
0000014707-22-000038
unlocatable
revenue
0000014707-22-000059
unlocatable
revenue
0000014707-22-000072
unlocatable
revenue
0000014707-23-000018
unlocatable
revenue
0000014707-23-000037
unlocatable
revenue
0000014707-23-000050
unlocatable
revenue
0000014707-23-000060
unlocatable
revenue
0000014707-24-000012
unlocatable
revenue
0000014707-24-000024
unlocatable
revenue
0000014707-24-000041
unlocatable
revenue
0000014707-24-000051
unlocatable
revenue
0000014707-25-000017
unlocatable
revenue
0000014707-25-000036
unlocatable
revenue
0000014707-25-000059
unlocatable
revenue
0000014707-25-000086
unlocatable
revenue
0000014707-26-000053
unlocatable
revenue
End of preview.

YAML Metadata Warning:empty or missing yaml metadata in repo card

Check out the documentation for more information.

Datasheet: smallprint SEC filings extraction corpus

Structured extraction from the primary financial statements of SEC 10-K and 10-Q filings into fifteen fields, each labelled with the XBRL fact the company itself filed. Built by smallprint on 2026-09-22. Every number below was written by the build; none was edited by hand.

Composition

7,874 items from 1,600 selected companies, filings dated 2022Q1 to 2026Q2, forms 10-K, 10-Q. Of 19,574 filings tried, 10,497 became items before the split and 9,077 were dropped with a named reason (below). The split then drops a further 2,623 training-pool filings dated after the cutoff.

Each item is one filing: text, the model's input (the cover page, the income statement, the balance sheet and, in an annual report, the audit signature, located and rendered from the filing's HTML with hidden inline XBRL removed); truth, the fifteen labels; and context, the reporting scale and the other periods' values of each line, which the grader uses to name a wrong-period reading. The median input is 6,561 characters.

Splits

Companies, not filings, are assigned to pools, so no company appears in both training and test. The cutoff, 2025-01-31, is the latest documented training cutoff of the base models; test-pool filings after it are the headline set, and before it the contamination comparison. Test filers appear in both test sets by design.

Split Filings Companies 10-K 10-Q
train 5,060 585 1,145 3,915
validation 713 88 161 552
test_pre_cutoff 1,396 165 287 1,109
test_post_cutoff 705 144 186 519

Fiscal periods: FY 1,779, Q1 2,079, Q2 2,009, Q3 2,007.

Where the labels come from

Numeric labels are XBRL facts from the SEC companyfacts API for the filing's own accession, for the period the report covers; cover-page labels are the filing's own inline XBRL tags. No model produced or checked any label. A filing is kept only when every label is printed in the section of the input its field is read from, within the grader's tolerance after the printed scale, so the task is extraction and not inference. The one exception is diluted weighted shares: when the income statement prints no share-count line at all, that label is null and the filing is kept (768 filings). The rules and their evidence are in docs/data.md.

Label coverage

Field Labelled Items
period_end 100% 7874
fiscal_period 100% 7874
revenue 100% 7874
cost_of_revenue 62% 4905
operating_income 88% 6931
net_income 100% 7874
eps_basic 88% 6957
eps_diluted 85% 6711
shares_diluted 79% 6245
total_assets 100% 7874
total_liabilities 89% 6987
cash_and_equivalents 100% 7874
stockholders_equity 100% 7874
auditor_name 22% 1770
state_of_incorporation 96% 7548

What is missing, and why

Reason Filings Share of those tried
truth_missing:revenue 3,214 16%
bank 1,140 6%
no_income_statement 949 5%
not_fetched 693 4%
no_balance_sheet 470 2%
unlocatable:auditor_name 403 2%
no_period 389 2%
unlocatable:revenue 344 2%
unlocatable:shares_diluted 314 2%
unlocatable:operating_income 191 1%
unlocatable:total_liabilities 184 1%
unlocatable:stockholders_equity 126 1%
truth_missing:stockholders_equity 103 1%
unlocatable:cash_and_equivalents 92 0%
unlocatable:eps_basic 90 0%
unlocatable:cost_of_revenue 88 0%
unlocatable:state_of_incorporation 63 0%
truth_missing:net_income 58 0%
unlocatable:total_assets 46 0%
truth_missing:cash_and_equivalents 35 0%
unlocatable:period_end 29 0%
unlocatable:eps_diluted 23 0%
truth_missing:total_assets 14 0%
unlocatable:net_income 8 0%
mixed_scale 7 0%
truth_invalid:cash_and_equivalents 4 0%

Underrepresented on purpose. Banks and savings institutions (industry codes 6021, 6022, 6029, 6035, 6036) are excluded: they report no single revenue line to label. Funds, trusts, business development companies and SPACs mostly drop out because they print no income statement of the kind the task reads, or no revenue. Filers whose statements print no reporting scale are dropped rather than labelled by guessing it. The corpus therefore underweights financial companies and very small or pre-revenue ones, and a score on it says nothing about extraction from their statements.

Collection

Fetched from SEC EDGAR under its fair-access policy: a declared contact address in every request, paced below ten requests a second, every response cached with its date and digest so the corpus rebuilds offline without refetching. Company selection is a keyed hash, seed 20270405. Rebuild with:

smallprint data build --first 2022Q1 --last 2026Q2 \
  --cutoff 2025-01-31 --companies 1600 --seed 20270405

Licence

SEC filings and XBRL data are public records of the US government. The licence under which this corpus is published is decided before publication and recorded here.

Checksums

13dc546b3d616ac9098c21a37ab784c9a285fb96bd5aa8e84ec0e461a13a0ed3  items.jsonl
82fb8d2506a9467bbe5cc22aa02bb71eb1baa597a47187a23c42405bc2745228  dropped.jsonl
242ce0ddb65e8ae01bf393623986004582fbe8260a30f0a6760743e2b2434cd6  report.json
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