Wed. Nov 29th, 2023

Content Assessment: Exploring the Inclusion of eDiscovery-Centric Resources in the Google C4 Dataset - A Highly Selective Search

Information - 93%
Insight - 92%
Relevance - 90%
Objectivity - 89%
Authority - 90%



A short percentage-based assessment of the qualitative benefit of the recent post highlighting the presence of selected eDiscovery resources in Google's C4 Dataset.

Editor’s Note: From time to time, ComplexDiscovery highlights publicly available or privately purchasable announcements, content updates, and research from cyber, data, and legal discovery providers, research organizations, and ComplexDiscovery community members. While ComplexDiscovery regularly highlights this information, it does not assume any responsibility for content assertions.

Contact us today to submit recommendations for consideration and inclusion in ComplexDiscovery’s data and legal discovery-centric service, product, or research announcements.

Background Note: The impact of organizations and entities on the output from Large Language Models (LLMs) can be more significant than one might initially anticipate. In some instances, specific resources within an industry can considerably influence how LLMs process and respond to information. One example of this influence can be observed by examining the Google C4 Dataset and searching for a non-comprehensive selection of domains from 55 eDiscovery-centric websites. While this exploration only offers a snapshot of selected resources from a non-all-inclusive list, it may provide valuable context for those evaluating the resource impact on LLMs and also highlight some tools that can help better understand the content populating LLMs. This deeper understanding can, in turn, contribute to shedding light on how selected eDiscovery resources may play a substantial role in shaping the knowledge and responses generated by LLMs – a role much more significant (or less important) than one might think.

Industry Backgrounder

Exploring the Inclusion of eDiscovery-Centric Resources in the Google C4 Dataset: A Highly Selective Search


Large language models, such as those developed by Google and OpenAI, are becoming increasingly sophisticated and pervasive in various industries. One such application of these models is in the eDiscovery ecosystem, which contains touchpoints ranging from cybersecurity and information governance to legal discovery. This article explores at a very high level the inclusion of selected eDiscovery-centric resources in the Google C4 Dataset. It also discusses why understanding this exploration may benefit professionals working in the eDiscovery ecosystem.

Google’s C4 Dataset and its Relevance to eDiscovery

Understanding the Google G4 Dataset

Google’s C4 (Colossal Clean Crawled Corpus) project aims to create a comprehensive and diverse dataset for training large language models. The dataset is built from web pages crawled by the CommonCrawl project and includes a diverse range of content in multiple languages. Google’s C4 Dataset serves as an essential foundation for developing more accurate and sophisticated language models that can understand and generate human-like text.

The C4 dataset from Google contains approximately 750GB of cleaned text data derived from CommonCrawl web pages. This large-scale dataset is utilized for training and improving large language models, such as those based on the GPT architecture.

CommonCrawl is an open-source initiative that crawls and archives publicly available web content. This vast repository of web-crawled data is invaluable for training large language models, as it provides a diverse and extensive source of text in multiple languages. The Common Crawl project significantly contributes to the C4 Dataset, enhancing its quality and usefulness for AI research.

The Role of large language models in eDiscovery

Large language models can potentially revolutionize the eDiscovery process by automating tasks ranging from document review to review reporting. These models can analyze vast amounts of data quickly and efficiently, identify relevant information, and generate insightful summaries or responses. As a result, they can save time, reduce costs, and improve the accuracy of eDiscovery outcomes.

Inclusion of eDiscovery-centric resources in the C4 Dataset

The presence of eDiscovery resources in the C4 Dataset is crucial for ensuring the accuracy and relevance of large language model outputs in the eDiscovery context. By training on high-quality eDiscovery resources, the models can better understand the domain-specific language, concepts, and best practices, leading to more reliable and valuable results for eDiscovery professionals.

ComplexDiscovery’s Non-Comprehensive List of eDiscovery Resources and Its Significance

Introduction to ComplexDiscovery’s resource listing

On March 9, 2023, ComplexDiscovery published a non-comprehensive list of potentially helpful eDiscovery-centric resources. These resources, ranging from analyst and research firms to industry associations and blogs, were designed to serve as a simple starting point for individuals seeking information related to eDiscovery. 

Selection of resources from ComplexDiscovery’s list for analysis

Given the manageable size of this resource listing and the direct or indirect relevance to the eDiscovery ecosystem of each listed resource, ComplexDiscovery created a truncated listing from an initial grouping of 100+ resources and used the top-level domain names of those resources to search the C4 Dataset. This truncation, which included the removal of top-level domain duplicates for multiple resources on the same domain and removing resources not available at the time of the Google C4 Dataset snapshot, resulted in a list of 55 resource domains.  

Top-level domain names search against the C4 Dataset

The objective of searching the top-level domain names of the selected resources within the C4 Dataset was to explore how a very targeted snapshot of eDiscovery resources might be represented in the C4 Dataset. This information on the representation of selected resources may help gauge how these resources are being used to train Google’s large language models in responding to inquiries and prompts related to eDiscovery.

The results of top-level domain name searches of 55 eDiscovery-centric resources are provided in the following table, as extracted from the C4 Dataset search capability resource featured in the Washington Post article titled “Inside the Secret List of Websites That Make AI Like ChatGPT Sound Smart.” The data is reported based on database rank, tokens, and the percentage of all tokens. The aggregated results for the selected resources below showcase the prevalence of content from these resources in the C4 Dataset.

Table: Selected eDiscovery Resources and the C4 Dataset

Resource Category (ComplexDiscovery)ResourceDomain SearchedRankTokens (Rounded)Percent of All Tokens
Analyst, Research, and Review FirmsG2G2.com15216,000,0000.01%
Analyst, Research, and Review FirmsCapterraCapterra.com21613,000,0000.008%
News, Announcement, and Commentary ResourcesLexologyLexology.com5198,100,0000.005%
Analyst, Research, and Review FirmsSoftware AdviceSoftwareAdvice.com7306,300,0000.004%
Associations, Consortiums, and GroupsIAPP (International Association of Privacy Professionals)IAPP.org5,2361,900,0000.001%
News, Announcement, and Commentary ResourcesJD SupraJDSupra.com5,2741,800,0000.001%
News, Announcement, and Commentary ResourcesLegaltech NewsLaw.com5,8981,700,0000.001%
Information and Research ResourcesNIST (National Institute of Standards and Technology)NIST.gov5,9201,700,0000.001%
Analyst, Research, and Review FirmsTrustRadiusTrustRadius.com6,9581,500,0000.001%
Information and Research ResourcesCybersecurity Legal Task Force (American Bar Association)AmericanBar.org8,2661,300,0000.0009%
Information and Research ResourcesFTC Premerger Notification Program (Federal Trade Commission)FTC.gov10,9591,100,0000.0007%
Analyst, Research, and Review FirmsGartnerGartner.com19,166720,0000.0005%
Industry BlogseDiscovery Team (Ralph Losey)E-DiscoveryTeam.com29,362530,0000.0003%
Analyst, Research, and Review FirmsIDCIDC.com41,812400,0000.0003%
Analyst, Research, and Review FirmsForresterForrester.com42,218400,0000.0003%
News, Announcement, and Commentary ResourcesLawSitesLawSitesblog.com63,769290,0000.0002%
Analyst, Research, and Review FirmsChambers and PartnersChambers.com77,729250,0000.0002%
Industry BlogsArtificial Lawyer (Richard Tromans)ArtificialLawyer.com85,162230,0000.0001%
Educational Training and ResourcesE-Discovery Team Traininge-DiscoveryTeamTraining.com93,748210,0000.0001%
News, Announcement, and Commentary ResourcesLexBlogLexBlog.com110,534180,0000.0001%
News, Announcement, and Commentary ResourcesLegalIT InsiderLegalTechnology.com122,034170,0000.0001%
eDiscovery Provider WebsitesRelativityRelativity.com145,664150,0000.00009%
Industry BlogseDisclosure Information Project (Chris Dale)ChrisDaleOxford.com187,731120,0000.00008%
News, Announcement, and Commentary ResourcesLegal IT ProfessionalsLegalITProfessionals.com220,976100,0000.00007%
Information and Research ResourcesENISA (European Union Agency for Cybersecurity)ENISA.Europa.eu271,14985,0000.00005%
Associations, Consortiums, and GroupsEDRM (Electronic Discovery Reference Model)EDRM.net293,31679,0000.00005%
eDiscovery Provider WebsitesIPROIPROTech.com299,99377,0000.00005%
Associations, Consortiums, and GroupsWomen in eDiscoveryWomenineDiscovery.org303,37977,0000.00005%
eDiscovery Provider WebsitesNuixNuix.com323,73372,0000.00005%
eDiscovery Provider WebsitesEpiqEpiqGlobal.com387,08261,0000.00004%
Analyst, Research, and Review FirmsComplexDiscoveryComplexDiscovery.com445,24853,0000.00003%
Associations, Consortiums, and GroupsACEDS (Association of Certified E-Discovery Specialists)ACEDS.org470,27550,0000.00003%
Industry BlogsHanzo Blog (Hanzo)Hanzo.co486,34849,0000.00003%
eDiscovery Provider WebsitesExterroExterro.com508,50246,0000.00003%
Associations, Consortiums, and GroupsThe Sedona Conference (TSC)TheSedonaConference.org508,61746,0000.00003%
Industry BlogsBall In Your Court (Craig Ball)CraigBall.net602,35939,0000.00002%
eDiscovery Provider WebsitesDiscoCSDisco.com747,83531,0000.00002%
eDiscovery Provider WebsitesHaystackIDHaystackID.com763,78130,0000.00002%
Information and Research ResourcesInternational Cyber Law in Practice: Interactive Toolkit (NATO CCDCOE)CCDCOE.org818,08228,0000.00002%
eDiscovery Provider WebsitesLogikcullLogikcull.com838,77827,0000.00002%
eDiscovery Provider WebsitesLexbeLexbe.com894,97326,0000.00002%
Associations, Consortiums, and GroupsILTA (International Legal Technology Association)ILTAnet.org929,14324,0000.00002%
eDiscovery Provider WebsitesLighthouseLighthouseGlobal.com1,049,92921,0000.00001%
eDiscovery Provider WebsitesKLDiscoveryKLDiscovery.com1,064,26221,0000.00001%
Information and Research ResourcesGDPR (General Data Protection Regulation) (European Union)GDPR.eu1,089,04320,0000.00001%
Associations, Consortiums, and GroupsCLOC (Corporate Legal Operations Consortium)CLOC.org1,200,57518,0000.00001%
Industry BlogsRide the Lightning (Sharon Nelson)SenseiEnt.com1,222,76318,0000.00001%
Information and Research ResourcesEDPB (European Data Protection Board)EDPB.Europa.eu1,306,89417,0000.00001%
Associations, Consortiums, and GroupsARMA InternationalArma.org1,321,94616,0000.00001%
Industry BlogsThe Cowen Group (David Cowen)CowenGroup.com1,637,48013,0000.000008%
Industry BlogseDiscovery Assistant Blog (Kelly Twigger)eDiscoveryAssistant.com1,757,03512,0000.000007%
Educational Training and ResourcesNordic Institute for Interoperability SolutionsNIIS.org2,609,5727,0000.000004%
Industry BlogsReveal Blog (George Socha and Cat Casey)RevealData.com5,437,0052,1000.000001%
Associations, Consortiums, and GroupsGICLI (The Government Investigations & Civil Litigation Institute)GICLI.org10,772,4223300.0000002%
eDiscovery Provider WebsitesL2 ServicesL2Services.net13,335,2851100.00000007%

Source: ComplexDiscovery and the Washington Post

Implications of eDiscovery Resource Representation in the C4 Dataset

Identifying potential biases and limitations

By analyzing the representation of eDiscovery resources in the C4 Dataset, professionals in the eDiscovery ecosystem can identify potential biases and limitations in the data used to train large language models. This knowledge may enable them to make more informed decisions about the reliability and applicability of AI-generated outputs in their work.

Enhancing the quality and diversity of data used to train large language models

Understanding the inclusion of eDiscovery resources in the C4 Dataset can also help researchers and developers improve the quality and diversity of data used to train large language models. By incorporating a more comprehensive range of eDiscovery-centric resources, models may become better equipped to generate more accurate and relevant responses in the eDiscovery context.

Addressing the needs of cybersecurity, information governance, and legal discovery professionals

By exploring the eDiscovery resources represented in the C4 Dataset, developers can better understand the needs of cybersecurity, information governance, and legal discovery professionals. This insight may allow them to fine-tune large language models to address better the unique challenges and requirements of the eDiscovery ecosystem, ultimately leading to more useful AI-generated outputs for these professionals.

Encouraging transparency in AI development

Highlighting the inclusion of eDiscovery-centric resources in the C4 Dataset emphasizes the importance of transparency in AI development. By understanding the data sources used to train large language models, professionals in the eDiscovery ecosystem may be able to evaluate the reliability of AI-generated outputs better and make more informed decisions about their adoption and integration into their work and workflows.


This high-level exploration of selected eDiscovery-centric resources in the Google C4 Dataset has meaningful implications for professionals in the eDiscovery ecosystem. Analyzing the representation of selected resources in the dataset may help identify potential biases and limitations, enhance the quality and diversity of data used to train large language models, and encourage transparency in AI development. It may also highlight, with context, resources that may have more influence than you would think on shaping LLM-driven answers to prompts and queries. As large language models continue to evolve and become more integrated into the eDiscovery ecosystem, understanding their data sources and potential limitations will be crucial in ensuring their successful application and adoption.

*Assisted by GAI and LLM Technologies

Article References

Additional Reading

Source: ComplexDiscovery


Generative Artificial Intelligence and Large Language Model Use

ComplexDiscovery OÜ recognizes the value of GAI and LLM tools in streamlining content creation processes and enhancing the overall quality of its research, writing, and editing efforts. To this end, ComplexDiscovery OÜ regularly employs GAI tools, including ChatGPT, Claude 2, Midjourney, and DALL-E3, to assist, augment, and accelerate the development and publication of both new and revised content in posts and pages published (initiated in late 2022).

ComplexDiscovery also provides a ChatGPT-powered AI article assistant for its users. This feature leverages LLM capabilities to generate relevant and valuable insights related to specific page and post content published on By offering this AI-driven service, ComplexDiscovery OÜ aims to create a more interactive and engaging experience for its users, while highlighting the importance of responsible and ethical use of GAI and LLM technologies.


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ComplexDiscovery is a distinguished digital publication that delivers journalistic insights into cybersecurity, information governance, and eDiscovery developments and technologies. It adeptly navigates the intersection of these sectors with international business and current affairs, transforming relevant developments into informational news stories. This unique editorial approach enables professionals to gain a broader perspective on the intricacies of the digital landscape for informed strategic decision-making.

Incorporated in Estonia, a nation celebrated for its digital innovation, ComplexDiscovery OÜ adheres to the most rigorous standards of journalistic integrity. The publication diligently analyzes global trends, assesses technological breakthroughs, and offers in-depth appraisals of services involving electronically stored information. By contextualizing complex legal technology issues within the broader narrative of worldwide commerce and current events, ComplexDiscovery provides its readership with indispensable insights and a nuanced understanding of the eDiscovery industry.