Alternative data datasets
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Metadata for every EDGAR filing submitted to the U.S. Securities and Exchange Commission from 1994 through December 14, 2024, derived from the quarterly master index files and including CIKs, issuer names, and form types.
patent_abstract_uspto is a text dataset of U.S. patent abstracts distributed under an MIT license and hosted on the Hugging Face Hub by publisher kaustav16. It contains roughly 9.36 million rows of patent identifiers paired with their corresponding abstract text.
Earnings Call LLM Insights 📚 Read the Full Story: For a deep dive into the methodology, the wildest moments we found, and key takeaways, check out the blog post:KnowTrend.ai: Auto-Grading Ten Years of Earnings Calls for Prescience and Delusion This dataset contains LLM-generated analysis of ~70,000+ earnings call transcripts. The analysis was performed using Kimi k2-0905-preview, focusing on extra
The patents-publications-dataset is a large-scale tabular collection of patent publication records distributed in Parquet format. Hosted by publisher labofsahil on the Hugging Face Hub under an unstated license, it is sized in the 100M–1B row range.
An API-based ClinicalTrials.gov scraper that retrieves over 585,000 study records including phase, sponsor, conditions, interventions, enrollment, eligibility, and sites, filterable by condition, sponsor, and status.
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.
The clinical_trials dataset distributes ClinicalTrials.gov registry records in Parquet format for offline analysis. It contains a single training split of roughly 150,000 rows sourced from the public clinical-trial registry.
Patent All Claims EP granted claim sets (indepdendent and dependent claims). One claim per line. Claims from 20210915-20250806 Splits Train: 96% Validation: 2% Test: 2% Usage from datasets import load_dataset ds = load_dataset("mhurhangee/ep-patent-all-claims")
A collection featuring the primary independent claim of United States utility patents issued between 2005 and 2025 is provided. Because the opening claim usually establishes the widest legal boundaries of an invention, it carries particular significance, and each entry includes the patent identifier alongside its claim text.
S&P 500 10-K topic tone profiles, FY2019–FY2026 Data version 0.4.0 (exported 2026-10-18; changes since 0.1.0 under Versioning). provenance.json records the version, the code commit, the model, hashes of the prompt and output schema, and the row count of every table. Tone scores for passages of S&P 500 10-K filings on five dimensions, toward 13 topics, by Claude Haiku 5.5 (claude-haiku-5-5). The re
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google-patents-data-preview is a community-uploaded preview of Google Patents bibliographic records, distributed in Parquet format through the Hugging Face Hub. The single training split contains roughly 340,000 rows covering patent identifiers, classifications, and localized text fields.
Global Job Postings – Multi-ATS is a single dated snapshot of 112,816 job listings aggregated from 23 applicant tracking systems and parsed into a 47-column schema by NextGig-Rocks. It is distributed as Parquet via the Hugging Face datasets library and targets labor-market research, not production job boards.
Over 1.3 million granted US patents from the BIGPATENT benchmark, each pairing its claims with an abstractive summary and full description text in English (CC BY 4.0, Parquet). Use it to track the technology areas where applicants are filing and to study how claim language has evolved over time.
TUDelft-Electricity-Consumption-1.0 is a high-resolution, open-source time series dataset of household electricity load published on Hugging Face by OpenSynth. It draws on multi-country trials covering thousands of households under different tariff regimes and is distributed in Parquet format.
Clinical-trial protocol documents from Parexel, tens of thousands of studies. Protocol text, covering inclusion criteria, endpoints and timelines, is a leading indicator for enrollment pace and pipeline risk.
Dataset card entry for "AIPD_nlp_granted_claims" with additional details required.
专利无效检索评测数据集 面向专利无效证据检索系统的公开 Benchmark，以权利要求文本为检索输入， 以真实无效案件中使用的证据文献为标准答案。 简体中文 · English 下载公开数据集 数据集简介 本数据集用于评估 AI Agent、检索模型和传统专利检索系统发现无效证据文献的能力。 每条样本包含待分析的权利要求、案件最终结果、证据文献，以及证据角色和法律依据等 结构化标注。 公开版本包含 80 条 Benchmark 样本，CN 与 US 各 40 条，覆盖 IPC 的 A–H 八个部。它既可以衡量系统能否找到至少一篇有效证据，也可以衡量系统对核心文献和 全部证据文献的覆盖程度。 这份数据可以用来评估什么 能力 说明 无效证据检索 给定权利要求文本，系统能否从专利文献中找到真实案件使用的无效证据 核心与完整召回 分别评估主要证据 primary_reference 和全部证据文献
PatSnap Patent OAR Bench A benchmark dataset for patent Office Action Response (OAR) tasks. The test split contains 40 cases: 13 CN, 13 EP, and 14 US. It includes 40 Office Action PDF documents totaling 229 pages, structured case materials, and 19 shared Judge-scored criteria per case (760 entries). Dataset: data/test.parquet, 40 cases in Parquet format. Office Action PDFs: assets/, named OAR-<id>
This dataset was created using LeRobot. Dataset Structure meta/info.json: { "codebase_version": "v2.1", "robot_type": "so100", "total_episodes": 50, "total_frames": 29874, "total_tasks": 1, "total_videos": 100, "total_chunks": 1, "chunks_size": 1000, "fps": 30, "splits": { "train": "0:50" }, "data_path": "data/chunk-{episode_chunk:03d}/episode_{episode_index:06d}.parquet", "video_path":… See the f
This dataset was created using LeRobot. Dataset Structure meta/info.json: { "codebase_version": "v2.1", "robot_type": "so100", "total_episodes": 50, "total_frames": 44746, "total_tasks": 1, "total_videos": 100, "total_chunks": 1, "chunks_size": 1000, "fps": 30, "splits": { "train": "0:50" }, "data_path": "data/chunk-{episode_chunk:03d}/episode_{episode_index:06d}.parquet", "video_path":… See the f
This dataset was created using LeRobot. Dataset Structure meta/info.json: { "codebase_version": "v2.1", "robot_type": "so100", "total_episodes": 20, "total_frames": 11940, "total_tasks": 1, "total_videos": 40, "total_chunks": 1, "chunks_size": 1000, "fps": 30, "splits": { "train": "0:20" }, "data_path": "data/chunk-{episode_chunk:03d}/episode_{episode_index:06d}.parquet", "video_path":… See the fu
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.
The nj-housing-prices-tabular dataset is a small tabular collection of New Jersey residential property listings, published on Hugging Face under an unstated license. It contains roughly 7,000 rows split across train, validation, and test partitions.
clinicaltrials.gov-summary_and_eligibility is a small Parquet mirror of selected ClinicalTrials.gov records, distributed on the Hugging Face Hub under the rjac publisher. It packages study identifiers, recruitment status, titles, brief summaries, and eligibility criteria into a single tidy table of roughly three thousand rows.
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.
A resource built for forecasting patent approval outcomes, introduced in research employing domain-specific fine-grained claim dependency graphs, with further documentation to be supplied later.
Dataset Card for "filtered_yelp_restaurant_reviews" More Information needed
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.
SEC EDGAR filings (processed) 🌐 The Fin AI Pretraining / reference corpus released by The Fin AI. Source: U.S. SEC EDGAR filings — https://www.sec.gov/search-filings. Note: Some parquet files in this repository are empty (0 bytes). Source Text extracted from public filings on the SEC EDGAR system. Structure Rows: 2,839,488 Columns: text Quick Start from datasets import load_dataset ds = load_datas
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A collection of Parquet files providing one record per Chinese invention patent family granted between 2003 and 2019, capturing a cumulative quality assessment pipeline that includes metrics such as semantic knowledge recombination, strict historical semantic novelty, and IPC-based robustness measures across global patent publications.
A 10% sample of over 573,000 ClinicalTrials.gov studies augmented with AI-classified therapeutic areas, sponsor categorization, outcome groupings, and duration metrics, offered for portfolio and market landscape analysis.
A 10% sample of a sponsor profiling resource containing entries for over 10,200 clinical trial sponsors, covering trial counts, completion ratios, phase distribution, therapeutic areas, and pipeline activity.
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.
Over 635,000 registered clinical studies from ClinicalTrials.gov together with a supplementary pharma intelligence table of roughly 1.06 million rows that map those trials to FDA drug approvals, distributed as part of an open data initiative for academic and personal use.
The Tech Job Postings & Salary Dataset from Zalize Data contains over 449,000 monthly job postings scraped from public applicant tracking systems at US and EU technology companies. It is distributed as parquet files under a CC BY-NC 4.0 license and is part of the DataForge Open Data program.