Alternative data datasets
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The clinical-trials-trec-topics dataset is a small tabular collection of clinical-trial topic records distributed in Parquet format on the Hugging Face Hub. It appears to be derived from TREC clinical-trial retrieval topics, with rows partitioned by year.
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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.
Vector embeddings of clinical-trial records, hundreds of thousands of entries in Parquet (Apache 2.0). Enables similarity and retrieval analysis of trial design, indication crowding and competitive positioning.
DAPFAM patent documents, a curated sample of US patents in Parquet with text for retrieval and classification tasks (CC BY-NC-SA 4.0). Scopus of claim text for building patent-similarity and technology-mapping models.
A curated, well-organized collection of documents formatted for straightforward ingestion into retrieval-augmented generation systems.
Content structured to serve as a retrieval-augmented knowledge foundation for a domain-specific research tool.
A curated corpus optimized for retrieval-augmented generation systems and semantic similarity queries.
Organized text collection well suited for retrieval-augmented generation, longitudinal language modeling, and dialogue-based data exploration.
Structured corpus optimized for retrieval-augmented generation and semantic similarity tasks, featuring duplicate removal, complete data fields, and substantial record counts.
Ready-to-use collection suited for retrieval-augmented question answering on historical medical topics.
Well-suited for embedding-based search and retrieval-augmented generation across a unified historical text collection.
Useful for retrieval-augmented legal history analysis, similarity-based search, and pretraining language models specialized in legal text.
A curated collection designed to function as a retrieval-augmented generation knowledge base and a resource for historical research.
A reference collection designed to support retrieval-augmented generation and the study of historical language models.
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.
Historical best bid and offer price records are made available through this dataset for retrieval and analysis.
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(
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.
FinSight gathers plain-text 10-K and 10-Q SEC filings for twenty major US public firms spanning six sectors, yielding 97 records intended for BERT fine-tuning, retrieval-augmented generation, and multi-agent financial research.
sec-filings is a Hugging Face dataset published by Sicheng-Chroma that distributes pre-chunked U.S. SEC filings paired with dense vector embeddings. It is distributed in optimized Parquet format and is intended for retrieval and similarity research over regulatory disclosures.
A snapshot of processed ClinicalTrials.gov records filtered to completed-recruitment Phase 3 and Phase 4 studies, plus trials of medical devices or behavioral interventions, totaling 156,887 trials as of March 2025, used for an agentic medical retrieval and evidence-grounding system.