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Markup

Turn text into structured data using GPT-4

Artificial Intelligence
GitHub
Tech
Data Science
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Hunted bySamuel DobbieSamuel Dobbie

Markup is a free & open-source annotation tool for transforming text into structured datasets that you can use to train ML models. Markup uses GPT-4 to learn how you annotate, so it can make smart suggestions and significantly speed up the process.

Top comment

Hey Product Hunt 👋 I'm super excited to share Markup with you—an open-source, AI-powered annotation tool for effortlessly transforming unstructured text into structured data for ML and NLP tasks like named-entity recognition. Markup learns as you annotate to predict and suggest complex annotations. In addition, Markup integrates seamlessly with widely-used and custom ontologies (e.g., UMLS) to help you quickly link concepts and ideas. Happy annotating 🚀

Comment highlights

Markup is a great and easy to use product which has made a big difference to the annotation parts of our natural language pipelines. Highly recommended for text annotation
As an academic plastic surgery registrar involved in developing and validating a NLP pipeline for skin cancer, I am thrilled to share my experience with Markup. Markup has played a crucial role in effortlessly transforming unstructured text into structured data, specifically for named-entity recognition in our skin cancer research. One of the standout features of Markup is its ability to learn and adapt as you annotate. This intelligent system predicts and suggests complex annotations, making the annotation process smoother and more efficient. This functionality has been immensely valuable in our research, as it has significantly reduced the time and effort required for manual annotation. Furthermore, Markup seamlessly integrates with widely-used and custom ontologies, such as UMLS, enabling quick and accurate linking of concepts and ideas. This feature has been particularly useful in our skin cancer research, where the precise identification and classification of medical terms and entities are critical. Peer-reviewed published papers where we have utilised Markup: https://www.ncbi.nlm.nih.gov/pmc... https://academic.oup.com/bjs/adv...
Markup has helped our clinical staff at Swansea University Health board annotate clinic letters at multiple sites. We have used it to produce gold standard annotations on our clinic letters across epilepsy, multiple sclerosis, cardiovascular and plastic surgery departments. The increase in AI tools is exciting, but for settings such as healthcare, we need a way to validate these tools against our own data. Markup allows this by making it easy for us to annotate our own data manually, and allow downstream models to be compared to those annotations. The best part about Markup is we can run it locally behind our own secure firewall as the code is open source! The GPT-4 annotation features looks great, and we are looking forward to making use of open-source alternative LLMs so that we can use them locally. Please see the following peer-reviewed published papers where we have used Markup in our analyses: https://www.frontiersin.org/arti... https://pubmed.ncbi.nlm.nih.gov/...

About Markup on Product Hunt

Turn text into structured data using GPT-4

Markup launched on Product Hunt on May 15th, 2023 and earned 73 upvotes and 4 comments, placing #29 on the daily leaderboard. Markup is a free & open-source annotation tool for transforming text into structured datasets that you can use to train ML models. Markup uses GPT-4 to learn how you annotate, so it can make smart suggestions and significantly speed up the process.

Markup was featured in Artificial Intelligence (466.5k followers), GitHub (41.2k followers), Tech (621.8k followers) and Data Science (3.8k followers) on Product Hunt. Together, these topics include over 269.4k products, making this a competitive space to launch in.

Who hunted Markup?

Markup was hunted by Samuel Dobbie. A “hunter” on Product Hunt is the community member who submits a product to the platform — uploading the images, the link, and tagging the makers behind it. Hunters typically write the first comment explaining why a product is worth attention, and their followers are notified the moment they post. Around 79% of featured launches on Product Hunt are self-hunted by their makers, but a well-known hunter still acts as a signal of quality to the rest of the community. See the full all-time top hunters leaderboard to discover who is shaping the Product Hunt ecosystem.

Reviews

Markup has received 3 reviews on Product Hunt with an average rating of 5.00/5. Read all reviews on Product Hunt.

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