frenchtext/bank-de-2401

Dataset Card for "bank de websites - 2401"

Dataset extracted from public websites by wordslab-webscraper in 2401:

• domain: bank
• language: de
• license: Apache 2.0

Dataset Sources

wordslab-webscraper follows the industry best practices for polite web scraping:

• clearly identifies itself as a known text indexing bot: "bingbot"
• doesn't try to hide the user IP address behind proxies
• doesn't try to circumvent bots protection solutions
• waits for a minimum delay between two pages to avoid generating too much load
• respects the website "robots.txt" indexing directives
• respects the web page Meta Robots HTML tag
• respects the web page X-Robots-Tag HTTP header
• respects the web page links rel=nofollow HTML attributes

The text data was extracted from the following websites:

Website	HTML pages	PDF docs	Words
bankenverband.de	806	140	779557
de.wikipedia.org	995	0	4085459
n26.com	50	0	31376
wirtschaftslexikon.gabler.de	5083	0	1185884
www.audi.de	527	1	403491
www.baaderbank.de	109	120	442164
www.bank-verlag.de	109	0	35299
www.bethmannbank.de	102	107	363744
www.bnpparibas.de	179	29	101685
www.bpb.de	1247	1	2962603
www.bundesbank.de	176	0	61572
www.businessinsider.de	1364	0	972937
www.bw-bank.de	310	0	240640
www.ca-autobank.de	61	13	45459
www.castell-bank.de	66	0	20902
www.db.com	117	3	109826
www.deutsche-bank.de	508	241	793933
www.dkb.de	439	0	207558
www.dzbank.de	417	239	2451792
www.ecb.europa.eu	86	1	74123
www.ethikbank.de	412	184	888045
www.financescout24.de	251	0	439369
www.finanzfluss.de	845	0	1524466
www.gladbacher-bank.de	195	0	108953
www.gls.de	367	33	405242
www.hanseaticbank.de	701	107	880371
www.ing.de	125	3	55793
www.kd-bank.de	124	44	129297
www.kfw.de	871	1685	6544379
www.l-bank.de	368	0	387263
www.mercedes-benz-bank.de	89	51	160132
www.nrwbank.de	478	278	2256593
www.onvista-bank.de	57	59	155342
www.postbank.de	1294	137	1489297
www.santander.de	223	288	587002
www.sozialbank.de	412	24	286188
www.sparda-bw.de	295	116	420822
www.sparkasse.de	672	0	551211
www.sumup.com	327	0	250632
www.t-online.de	1473	0	1137214
www.targobank.de	166	90	323461
www.tomorrow.one	319	0	213777
www.triodos.de	280	25	393058
www.unionbank.de	247	31	225218
www.vrdh.de	193	0	102936
www.vwfs.de	605	184	1090987
www.wiwo.de	1209	0	628824
www.ziraatbank.de	57	105	256946

Uses

WARNING

• the text included in this dataset belongs to its original authors and is protected by copyright laws
• you are not allowed to use this dataset for anything else than training a large language model
• when using a large language model trained on this dataset, you will need to ensure that you comply with the law
• if you benefit from this large language model, you should try to share the value with the original text authors

wordslab-webscraper uses an advanced Html to text conversion algorithm optimized for long context language modeling:

• tries to recover the logical structure of the document from the Html or PDF layout
• preserves document / section / list / table grouping and nesting information
• deduplicates text at the website level while preserving the document structure

Each example in this dataset is a markdown text conversion of a full HTML page or PDF document:

• the document structure is preserved by markdown syntax: headers, lists, tables, paragraphs
• all duplicate paragraphs are removed

Dataset Structure

The dataset is divided in 3 splits:

• train: 80% of the data
• valid: 10% of the data
• test: 10% of the data

wordslab-webscraper generates one parquet file per website and per split.

The parquet files are named with the following pattern:

• bank_de_2401_[split]_[website].parquet

Note than you can load individual splits or websites with HuggingFace datasets using the following commands:

from datasets import load_dataset

# Load a single plit
dataset = load_dataset("namespace/bank-de-2401", split="train")

# Load a single website
data_files = { "train": "bank_de_2401_train_[website].parquet", "valid": "bank_de_2401_valid_[website].parquet", "test": "bank_de_2401_test_[website].parquet" }
dataset = load_dataset("namespace/bank-de-2401", data_files=data_files)

Each example in the dataset contains the text of a full web page or PDF document, with the following features:

• Uri: string
• ExtractedFromPDF: bool
• Timestamp: string
• Lang: string
• Title: string
• Text: string
• Words: int32
• AvgWordsLength: int32
• Chars: int32
• LetterChars: int32
• NumberChars: int32
• OtherChars: int32

Note that beause each example is a full page or document, the "Text" feature can be a pretty long string containing thousands of words (as measured by the "Words" feature): you will typically need to chunk it down to the context size of your large language model before using it.

Bias, Risks, and Limitations

This dataset is a direct extraction from the source websites.

It was not manually curated to remove misleading, offensive, or harmful content.

Please add a filtering step before using it to train a large language model if the source websites can't be trusted.

Dataset Card Contact

Please add a comment in the community section of this repository if you want the maintainer to add or remove websites from this dataset.