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Datasets:
dacheah
/
aml-sanctions-law-corpus

Tasks:
Text Retrieval
Text Classification
Languages:
German
English
Japanese
Size:
1K<n<10K
Tags:
legal
law
provenance
legal-nlp
rag
License:
Dataset card Data Studio Files
xet
 Community
1
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The dataset viewer is not available for this split.
Cannot load the dataset split (in streaming mode) to extract the first rows.
Error code:   StreamingRowsError
Exception:    TypeError
Message:      Couldn't cast array of type timestamp[s] to null
Traceback:    Traceback (most recent call last):
                File "/src/services/worker/src/worker/utils.py", line 147, in get_rows_or_raise
                  return get_rows(
                      dataset=dataset,
                  ...<4 lines>...
                      column_names=column_names,
                  )
                File "/src/libs/libcommon/src/libcommon/utils.py", line 272, in decorator
                  return func(*args, **kwargs)
                File "/src/services/worker/src/worker/utils.py", line 127, in get_rows
                  rows_plus_one = list(itertools.islice(safe_iter(ds, dataset=dataset), rows_max_number + 1))
                File "/src/services/worker/src/worker/utils.py", line 478, in safe_iter
                  yield from ds.decode(False) if ds.features else ds
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2818, in __iter__
                  for key, example in ex_iterable:
                                      ^^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2355, in __iter__
                  for key, pa_table in self._iter_arrow():
                                       ~~~~~~~~~~~~~~~~^^
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2380, in _iter_arrow
                  for key, pa_table in self.ex_iterable._iter_arrow():
                                       ~~~~~~~~~~~~~~~~~~~~~~~~~~~~^^
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 536, in _iter_arrow
                  for key, pa_table in iterator:
                                       ^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 419, in _iter_arrow
                  for key, pa_table in self.generate_tables_fn(**gen_kwags):
                                       ~~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^
                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 2369, in table_cast
                  return cast_table_to_schema(table, schema)
                File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2303, in cast_table_to_schema
                  cast_array_to_feature(
                  ~~~~~~~~~~~~~~~~~~~~~^
                      table[name] if name in table_column_names else pa.array([None] * len(table), type=schema.field(name).type),
                      ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                      feature,
                      ^^^^^^^^
                  )
                  ^
                File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 1852, in wrapper
                  return pa.chunked_array([func(chunk, *args, **kwargs) for chunk in array.chunks])
                                           ~~~~^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2143, in cast_array_to_feature
                  return array_cast(
                      array,
                  ...<2 lines>...
                      allow_decimal_to_str=allow_decimal_to_str,
                  )
                File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 1854, in wrapper
                  return func(array, *args, **kwargs)
                File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2005, in array_cast
                  raise TypeError(f"Couldn't cast array of type {_short_str(array.type)} to {_short_str(pa_type)}")
              TypeError: Couldn't cast array of type timestamp[s] to null

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AML/CTF & Financial-Sanctions Legal Corpus (UN · Australia · UK · US · EU · Canada · Singapore · Switzerland · Hong Kong · Japan · UAE, v1)

A neutral, provenance-first, machine-readable record of the law of anti-money-laundering / counter-terrorism-financing (AML/CTF) and financial sanctions across ten cross-referenced jurisdictions — Australia, the United Kingdom, the United States, the European Union, Canada, Singapore, Switzerland, Hong Kong, Japan and the United Arab Emirates — rooted in the UN treaty and Security Council backbone, with the FATF 40 Recommendations as the connective spine. Every record carries its official source, retrieval date, citation, jurisdiction, legal status, language, an authoritative-status flag, and a SHA-256 content hash; every change is a new dated version.

Why this dataset is different

Most legal datasets are scraped text with no sourcing. Here every row is traceable: the authoritative text is stored in its authentic language with a content hash and a fidelity flag, and anything generated (concept tags, structure) is kept in a separate, clearly-labelled layer. That makes it low-risk input for retrieval-augmented generation and citation-grounded legal NLP.

Configs

documents — one row per instrument version: the full authoritative text plus provenance (source_url, official_citation, authoritative_status, text_fidelity, content_hash, license, rights_note, provenance_note, dates, jurisdiction, language).

provisions — one row per structural unit (article / section / principle / guideline): the unit text, its neutral concepts (curated (human-reviewed) for the main instruments, keyword-derived elsewhere; unofficial), and a link back to the source instrument's text hash and URL. Ideal as pre-chunked, concept-labelled context for RAG.

from datasets import load_dataset
docs = load_dataset("dacheah/aml-sanctions-law-corpus", "documents")
prov = load_dataset("dacheah/aml-sanctions-law-corpus", "provisions")

Contents

Instrument Jurisdiction Adopted Fidelity
Federal AML/CFT Law 2018 (superseded) ARE 2018-09-23 extracted_verified
Federal AML/CFT Law 2025 ARE 2025-10-14 extracted_verified
Combating Terrorism Crimes Law 2014 ARE 2014-08-20 extracted_verified
AML/CFT Implementing Regulation 2019 ARE 2019-02-28 extracted_verified
TFS / UN-sanctions mechanism 2020 ARE 2020-11-15 extracted_verified
AML/CTF Act 2006 AUS extracted_verified
AML/CTF Act 2006 AUS extracted_verified
AML/CTF Act 2006 AUS extracted_verified
AML/CTF Amendment Act 2024 AUS 2024-12-10 extracted_verified
Autonomous Sanctions Act 2011 AUS extracted_verified
Charter of the United Nations Act 1945 AUS extracted_verified
Autonomous Sanctions Regulations 2011 AUS extracted_verified
AML/CTF Rules 2025 AUS extracted_verified
AML/CTF Transitional Rules 2026 AUS extracted_verified
Criminal Code (AML/CTF offences) CAN extracted_verified
FACFOA CAN extracted_verified
JVCFOA (Magnitsky) CAN extracted_verified
PCMLTFA CAN extracted_verified
SEMA CAN extracted_verified
United Nations Act (CA) CAN extracted_verified
PCMLTFR CAN extracted_verified
AMLA / GwG CHE extracted_verified
Criminal Code (AML/CTF articles) CHE extracted_verified
Embargo Act / EmbG CHE extracted_verified
AMLO / GwV CHE extracted_verified
AMLO-FINMA / GwV-FINMA CHE extracted_verified
4AMLD (Dir (EU) 2015/849) EU extracted_verified
AMLD6 (Dir (EU) 2024/1640) EU extracted_verified
AMLA Reg (Reg (EU) 2024/1620) EU extracted_verified
AMLR (Reg (EU) 2024/1624) EU extracted_verified
FATF Recommendations international None
ECCTA 2023 GBR 2023-10-26 extracted_verified
ECTEA 2022 GBR 2022-03-15 extracted_verified
POCA 2002 GBR extracted_verified
SAMLA 2018 GBR extracted_verified
Terrorism Act 2000 GBR 2000-07-20 extracted_verified
MLR 2017 GBR extracted_verified
AMLO HKG extracted_verified
CBMCBNI Ordinance HKG extracted_verified
DTROP HKG extracted_verified
OSCO HKG extracted_verified
UNATMO HKG extracted_verified
UNSO HKG extracted_verified
WMD(CPS)O HKG extracted_verified
Organized Crime Punishment Act JPN extracted_verified
APTCP (犯収法) JPN extracted_verified
FEFTA (外為法) JPN extracted_verified
International Terrorist Asset-Freezing Act JPN extracted_verified
Terrorist Financing Punishment Act JPN extracted_verified
CDSA SGP extracted_verified
PSPM Act 2019 SGP extracted_verified
TSOFA SGP extracted_verified
United Nations Act (SG) SGP extracted_verified
UN (Anti-Terrorism Measures) Regs SGP extracted_verified
Palermo Convention 2000 (UNTOC) international extracted_verified
Terrorist Financing Convention 1999 international extracted_verified
UNCAC 2003 (Mérida) international 2003-10-31 extracted_verified
Vienna Convention 1988 international extracted_verified
UNSCR 1267 (1999) international extracted_verified
UNSCR 1373 (2001) international extracted_verified
UNSCR 1540 (2004) international extracted_verified
31 C.F.R. Part 1010 USA extracted_verified
18 U.S.C. §1956 USA extracted_verified
18 U.S.C. §1957 USA extracted_verified
18 U.S.C. §2339A USA extracted_verified
18 U.S.C. §2339B USA extracted_verified
18 U.S.C. §2339C USA extracted_verified
BSA (31 U.S.C. §§5311–5336) USA extracted_verified
IEEPA (50 U.S.C. §§1701–1708) USA extracted_verified

Licensing

Mixed, and recorded per record. The compilation, structure, and concept tags (the derived layer) are CC BY 4.0. Source texts are not relicensed — each keeps its own terms (e.g. Commonwealth of Australia legislation under CC BY 4.0; UK legislation Crown copyright under OGL v3.0; UN official documents free to reproduce with attribution; FATF/OECD material under copyright, restricted), recorded in every row's license / rights_note. See NOTICE.

Disclaimer

This is a reference record, not legal advice. The authoritative text of each instrument is the original in its authentic language; translations and concept tags are unofficial and derived (concept tags are unofficial and derived — expect occasional over/under-tagging). Always confirm against the cited official source for anything legally operative.

Citation 

AML/CTF & Financial-Sanctions Legal Corpus (UN · Australia · UK · US · EU · Canada · Singapore · Switzerland · Hong Kong · Japan · UAE, v1) (Dan Cheah). https://github.com/dacheah/aml-sanctions-law-corpus

Dataset generated from the repository by scripts/export_hf_dataset.py on 2026-07-11 — do not edit by hand.
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