Alternative data datasets
Browse by provider, category, marketplace, access, delivery and license
A reconstructed EDGAR corpus of company filings in English (Apache 2.0): a large sample of annual and quarterly reports and exhibits, hundreds of thousands of records. Comparable to other public SEC text sets and a solid starting point for filings-based research.
Monthly petabyte-scale crawls of the open web published as WARC segments with a CDX index service for targeted retrieval: raw material for language models, market mapping and large-scale entity extraction.
A curated corpus optimized for retrieval-augmented generation systems and semantic similarity queries.
This collection shows high suitability for machine learning model development and retrieval-augmented generation workflows.
A corpus of SEC EDGAR filings in English (Apache 2.0), roughly a few hundred thousand company documents including annual and quarterly reports and exhibits. The filings text is organized for model pretraining and retrieval, but the same documents are the raw material for filings-based and disclosure signals.
Layout metadata produced by PatentHubLayoutV2 for a JusticeDAO repository holding patent and legal material. It references the CFR Title 37 annual edition for 2024 and carries the tag patent-legal-v2.0.0, with publication handled separately as an operator decision.
The Future of Patent Corpus Management One Document, Fully Decoded - Without Anyone Reading It The signal you cannot get from a search interface The highest-value competitor signal in a patent portfolio is not the invention. It is the amount of money and urgency a company committed to it. That signal is never in an abstract, and no search interface surfaces it. It comes out of this corpus for ever
View source information and access options.
The ja_patent mirror of llm-jp-corpus-v4, assembled by the LLM-jp Corpus Building Working Group at NII, reproduces the Japanese patent sub-corpus from the larger LLM-jp Corpus v4 release. It is delivered as 621 jsonl.gz files totaling 58.2 GB in compressed form, with each line holding a JSON object that includes a text field and a meta field containing the document identifier, URL, and other provenance information.
Citation This dataset builds on edgar-corpus.
Public access to SEC filings and related submissions/XBRL data APIs. Filing forms differ in scope, structure and reporting delay; amendments and publication timestamps matter for historical research.
Keyword frequencies, LDA topics & store counts from SEC EDGAR (FY1996-2025)
The job-postings-english-clean dataset, published by 2024-mcm-everitt-ryan, is an English-language corpus of online job postings distributed as a single Parquet train split of roughly 1.76 million rows. It is tagged as US-region data and is intended for text-based machine learning workflows.
About 1.5 million US patent claims split into training and test partitions in CSV, organized for claim-level classification and summarization work (Apache 2.0). A large, ready-split corpus for IP-claims modeling.
EDGAR_FILINGS_DATASET_2022_2026H1 is a Hugging Face dataset that compiles parsed SEC EDGAR filings into a single tabular corpus. It covers roughly 2022 through the first half of 2026 and is distributed as Parquet with about 1.7 million records.
A leak-free, chronologically ordered corpus of 8-K, 10-Q, and 10-K filings for roughly 610 present-day U.S. large-cap companies, each paired with objective forward-return labels through 2026. The release is structured as a benchmark for testing whether filing language can anticipate subsequent stock performance, with clearly separated provenance classes.
GenAI-job-postings-Dataset is a small, US-focused text corpus of generative-AI and machine-learning job postings distributed in Parquet format. The dataset is published on the Hugging Face Hub under an unstated license and comprises a single train split of roughly 120 rows.
A labeled corpus used to teach machine learning models how to detect sentiment and emotional cues in written language.
Curated training corpus with an AI Readiness Score of 84 out of 100, positioned for regulated industry model development.
Curated and audited corpus drawing from two leading obstetrics and gynecology journals, formatted for artificial intelligence workflows.
Structured corpus optimized for retrieval-augmented generation and semantic similarity tasks, featuring duplicate removal, complete data fields, and substantial record counts.
Quarterly 10-Q filings parsed from EDGAR into JSON, millions of records in English (MIT). The quarterly companion to the 10-K corpus for tracking sequential changes in operating performance and risk factors.
Dataset Card for clinicaltrials/2017 The clinicaltrials/2017 dataset, provided by the ir-datasets package. For more information about the dataset, see the documentation. Data This dataset provides: docs (documents, i.e., the corpus); count=241,006 This dataset is used by: clinicaltrials_2017_trec-pm-2017, clinicaltrials_2017_trec-pm-2018 Usage from datasets import load_dataset docs = load_dataset(
Earnings-call transcripts from an IBM research project, tens of thousands of records with finance tags, in CC0. A filings-adjacent corpus for call-tone and question-and-answer analysis.
10-K filings for S&P 500 companies retrieved from EDGAR, stored as Parquet with the filing text attached (MIT). A focused corpus for the large-cap annual disclosure cycle: risk factors, MD&A and segment detail for every S&P 500 name.
The Patent Legal IR GraphRAG release follows the Publicus retrieval format, providing dense corpus shards, BM25 documents with CID-keyed length and entry metadata, and BM25 postings arranged for inverted-index use.
Restaurant_Reviews.tsv is a small text corpus of customer restaurant reviews paired with a binary sentiment label. It is published on the Hugging Face Hub by user KarthikaRajagopal under an unstated license.
Corpus of 32 DV cheat sheets, 32 DV charts and 7 recommended DV books
A corpus of around 1.3 million U.S. patent filings paired with human-authored abstractive summaries, organized into nine Cooperative Patent Classification categories ranging from human necessities to textiles and paper.
A compact sample set of SEC filings used for the MemGPT agent demos, tens of thousands of text records. A small, clean entry point to filings text rather than a comprehensive corpus.
german-job-postings is a publicly hosted corpus of roughly 70,584 normalized German-language vacancies drawn from the Bundesagentur für Arbeit Jobbörse API, each row tagged with the KldB-2010 occupation code and machine-assigned ESCO occupation and skill labels. The dataset is distributed under CC-BY-4.0 and is intended as an open alternative to the predominantly English/US job-posting resources available to machine-learning practitioners.
The restaurant_reviews dataset is a small text corpus of roughly one thousand customer review snippets paired with binary sentiment labels, published on the Hugging Face Hub under the user account pachequinho. It is distributed in CSV format with an Apache-2.0 license declaration.
Patent_FR_US_Merge_Radix_65536 is a Hugging Face dataset by publisher PhysiQuanty that merges French and US patent documents into a single text corpus. It is distributed in Parquet format and is tagged with an Apache-2.0 license, though the README provides no further description.
patent-ate termhood on HUPD This dataset is a ranked phrase table: each row is a multiword (or surface) key, a nested-frequency C-value, and how many filings contain that key (df). patent-ate corpus then score built it from the Harvard USPTO Patent Dataset (HUPD). It is not HUPD itself. Start with the slice (3,393 rows, tens of kilobytes). The full table is 88,607,764 keys from 4,518,254 filings a
**First end-to-end UAVs-security corpus
An English-language NLP corpus of cleaned earnings call transcripts gathered from public investor-relations pages, sized between 10,000 and 100,000 documents for financial analysis and LLM work.
The us-patents dataset is a collection of ~ 8M US patent grants and applications from 1976-2025, cleaned, filtered, and formatted for pre-training of language models. Document Format corpus_id: Unique integer key with no semantic value. filing_date: The filing date of the grant or application. In case of duplicates, earliest filing date from the duplicate cluster. patent_type: The type of patent.
Text of SEC filings pulled from EDGAR spanning millions of records in English (Apache 2.0): 10-K, 10-Q, 8-K, annual reports and exhibits, tagged for text-generation and classification. A practical base corpus for earnings- and filings-driven signals, from risk factors and MD&A to management commentary.
PatentPulse PatentPulse is a provenance-preserving corpus of USPTO grants and published patent applications extracted from official weekly XML bulk releases. This immutable Parquet snapshot normalizes the project's historical append-only JSONL into one schema. Historical partial snapshot. This release was captured on 2026-08-28 while the upstream backfill was still in progress. It is a stable, cit
10-K annual filings from EDGAR in Parquet, tens of thousands of documents. The standard annual-disclosure corpus for fundamentals, risk-factor and management-discussion analysis.