Natural Language Processing (NLP) Data: Definiton, Examples & Datasets
- Overview
- Datasets
- Providers
- Use Cases
- Attributes
- FAQ
- Overview
- Datasets
- Providers
- Use Cases
- Attributes
- FAQ
What is Natural Language Processing (NLP) Data?
NLP data refers to any form of textual information that is used for training or evaluating natural language processing models. It includes text documents, speech transcripts, social media posts, customer reviews, and more. NLP data is processed and analyzed using machine learning algorithms to understand and extract meaning from human language, enabling tasks like sentiment analysis, language translation, chatbots, and text summarization.
Examples of Natural Language Processing (NLP) data include text documents, social media posts, customer reviews, chat logs, and news articles. NLP data is used for tasks such as sentiment analysis, language translation, text classification, named entity recognition, and speech recognition. In this page, you’ll find the best data sources for NLP data.
Best Natural Language Processing (NLP) Databases & Datasets
Here is our curated selection of top Natural Language Processing (NLP) Data sources. We focus on key factors such as data reliability, accuracy, and flexibility to meet diverse use-case requirements. These datasets are provided by trusted providers known for delivering high-quality, up-to-date information.
Audio Annotation Services | AI-assisted Labeling |Speech Data | AI Training Data | Natural Language Processing (NLP) Data
In-Cabin Speech Data | 15,000 Hours | AI Training Data | Speech Recognition Data | Audio Data |Natural Language Processing (NLP) Data
Machine Learning (ML) Data | 800M+ B2B Profiles | AI-Ready for Deep Learning (DL), NLP & LLM Training
Canaria | Salary Data | US | 25M+ Monthly Job Postings & 2 Year Historical | AI-LLM Enhanced Salary Data
Native & Accented English Speech Data |40,000 Hours | Audio Data|Speech Recognition Data| Natural Language Processing (NLP) Data
Nordic B2B Profiles Data | B2B Marketing Data | 10M Verified Leads for Norway, Sweden & Finland (100+ Attributes)
AI & ML Training Data | Artificial Intelligence (AI) | Machine Learning (ML) Datasets | Deep Learning Datasets | Easy to Integrate | Free Sample
Raw ESG Data | Controversy Screening for 10K+ companies
FileMarket | 20,000 pictures | Object Detection Data | AI Training Data | Deep Learning (DL) Data| Gesture Recognition / Machine Learning (ML) Data
Foundation Model Data Collection and Data Annotation | Large Language Model(LLM) Data | SFT Data| Red Teaming Services
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Top Natural Language Processing (NLP) Data Providers & Companies
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Nexdata
CoverageUSAUK+184Founded in 2011, Nexdata has grown to be a globally renowned AI training data service company. Nexdata owns an extensive library of off-the-shelf datasets and provides flexible data collection, annotation and curation services.Volume1M Hours Speech, 800TB ImageAccuracyAbove 95%CopyrightCollected with Consent -
Coresignal
CoverageUSAUK+247VCoresignal has strong demographic and firmographic datasets both on quality and volume while keeping the data as fresh as it can be. We've been using Coresignal for years and we can only speak highly about the product and team behind it. Highly recommended.
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StageZero
CoverageNorwayBulgaria+1We are a Helsinki, Finland-based AI data company and innovator of the ground-breaking MicroTasks technology used for ethical data creation and labeling.Trusted byBillion $ companies1k+ usersAvailable instantlyEUCoverage -
TAUS
CoverageUSAUK+32MOracle International Product Solutions has worked with TAUS on a joint pilot project to enable data discovery within TAUS's Data Cloud corpora. The process consisted in Oracle IPS supplying TAUS with a sample of approximately 30K English strings, representing content that is aligned to Oracle projects. TAUS used the sample to explore Data Cloud for similarity & proximity, across 5 languages, and reverted back with three categories of data output, with score ranges on similarity and proximity. Oracle IPS then performed a linguistic assessment of this output. Our in-depth linguistic review rendered positive results and the content supplied by TAUS was of good quality, appropriate to consume as aligned corpora to that supplied in the Oracle sample with an average score of 84% for across the 5 languages. Oracle IPS will continue to work with TAUS to assess the effect that consuming this discovered corpora will have on engine quality. We look forward to having data search and discovery features on Data Cloud, whereby a user is capable of discovering their own project aligned content as a consumable self-service. We believe this will allow TAUS and its members to drive increased value from the TAUS data assets and in turn will likely continue to fuel growth in the pool of data and value-add services.
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WayWithWords
CoverageSouth AfricaVWe partnered with WayWithWords on AI Data Collection (simulating spontaneous conversations), Transcription, and Annotation services in multiple languages, including UK English, AU English, ZA English, and Afrikaans. It was a pleasure working with the team at WayWithWords, as they are very professional, communicative, and organized.
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Overtone
CoverageUSAUK+188We analyse online texts – news, blogs, comments, PR, reports – for qualitative signals. These intrinsic data points are used to assess impact, depth, human effort and audience investment. We are currently running in English and Spanish.90%Human expert matching5xContent type distinctions4000+Global news sources
Popular Use Cases for Natural Language Processing (NLP) Data
Natural Language Processing (NLP) Data is essential for a wide range of business applications, offering valuable insights and driving opportunities across industries. Below, we have highlighted the most significant use cases for Natural Language Processing (NLP) Data.
Main Attributes of Natural Language Processing (NLP) Data
Below, we outline the most popular attributes associated with this type of data—features that data buyers are actively seeking to meet their needs.
| Attribute | Type | Description | Action |
|---|---|---|---|
| String | The name of a language as per ISO 639. | View 4 datasets | |
| String | The name of a company or business, might be the legal or brand name. | View 2 datasets | |
| String | The name of a city. | View 1 datasets | |
| String | The industry classification of a company. | View 1 datasets | |
| String | The name of a country. | View 1 datasets | |
| String | The International Securities Identification Number (ISIN). | View 1 datasets |
Frequently Asked Questions
How is the Quality of Natural Language Processing (NLP) Data Maintained?
The quality of Natural Language Processing (NLP) Data is ensured through rigorous validation processes, such as cross-referencing with reliable sources, monitoring accuracy rates, and filtering out inconsistencies. High-quality datasets often report match rates, regular updates, and adherence to industry standards.
How Frequently is Natural Language Processing (NLP) Data Updated?
The update frequency for Natural Language Processing (NLP) Data varies by provider and dataset. Some datasets are refreshed daily or weekly, while others update less frequently. When evaluating options, ensure you select a dataset with a frequency that suits your specific use case.
Is Natural Language Processing (NLP) Data Secure?
The security of Natural Language Processing (NLP) Data is prioritized through compliance with industry standards, including encryption, anonymization, and secure delivery methods like SFTP and APIs. At Datarade, we enforce strict policies, requiring all our providers to adhere to regulations such as GDPR, CCPA, and other relevant data protection standards.
How is Natural Language Processing (NLP) Data Delivered?
Natural Language Processing (NLP) Data can be delivered in formats such as CSV, JSON, XML, or via APIs, enabling seamless integration into your systems. Delivery frequencies range from real-time updates to scheduled intervals (daily, weekly, monthly, or on-demand). Choose datasets that align with your preferred delivery method and system compatibility for Natural Language Processing (NLP) Data.
How Much Does Natural Language Processing (NLP) Data Cost?
The cost of Natural Language Processing (NLP) Data depends on factors like the datasets size, scope, update frequency, and customization level. Pricing models may include one-off purchases, monthly or yearly subscriptions, or usage-based fees. Many providers offer free samples, allowing you to evaluate the suitability of Natural Language Processing (NLP) Data for your needs.
What Are Similar Data Types to Natural Language Processing (NLP) Data?
Natural Language Processing (NLP) Data is similar to other data types, such as Translation Data and Transcription Data. These related categories are often used together for applications like Deep Learning and Data Science.
