Life & fun · alternatives · 2026
24 alternatives to Rules-based labelling tool for NLP
This is a rules-based labelling tool designed for natural language processing tasks. It helps users create and apply custom labelling rules to text data without requiring machine learning models. The tool is available… Below are 24 products that do a similar job, ranked by how close each is in meaning and then by launch-day votes. Rules-based labelling tool for NLP launched in 2021; newer entries below may have overtaken it.
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The easy way to turn text into structure data
2021 · getmarkup.com · its alternatives →
- 2NL
Link: https://www.nlpdemystified.org/ Hi HN: After a year of work, I've published my free NLP course. The course helps anyone who knows Python and a bit of math go from the basics to today's mainstream models and frameworks. I strive to balance theory and practice, so every module consists of detailed explanations and slides along with a Colab notebook putting the ideas into practice (in most modules). The notebooks cover how to accomplish everyday NLP tasks including extracting key information, document search, text similarity, text classification, finding topics in…
2022 · its alternatives →
- 3AL
Hi HN! I am Maria, solo founder of DataQA (https://dataqa.ai/), a tool to search and label documents for various NLP tasks (e.g. entity extraction, entity linking, etc). I have worked as a data scientist and ML engineer for the better part of a decade, and over that time have specialised mainly in applications involving natural language processing (NLP). One of the key questions I have always had at the back of my mind is whether my time was well spent. Whenever I spent more time on feature engineering or trying different models, I always wondered whether I would get better…
2021 · its alternatives →
- 4
Open source data labelling platform for AI model tuning
2023 · labelstud.io · its alternatives →
- 5IC
Improving the way car crashes are reported in local media by using natural language processing to identify editorial anti-patterns that obscure the preventable nature of crashes.
2021 · visionzeroreporting.com · its alternatives →
- 6
Natural language API using Google machine learning
2016 · cloud.google.com · its alternatives →
- 7
DeepTagger▲386Hi HN, I built a tool for teaching LLMs how to extract structured data from documents by annotating, not prompt engineering. I’d love your feedback. How it works: - Upload a document (DOCX, PDF, image, etc.) - Select and tag parts of it (supports nesting, arrays, custom tag structures) - Upload another document → click "predict" → see editable annotations - Amend them and save as a new example - Call the API with a third document → get JSON back Use cases: - Identify "important clauses" in contracts - Extract "total value" from invoices - Anything subjective, like "healthy ingredients" on a…
2025 · deeptagger.com · its alternatives →
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- 10
Hi HN! I'm excited to share Autolabel, an open-source Python library to label and enrich text datasets with any Large Language Model (LLM) of your choice. We built Autolabel because access to clean, labeled data is a huge bottleneck for most ML/data science teams. The most capable LLMs are able to label data with high accuracy, and at a fraction of the cost and time compared to manual labeling. With Autolabel, you can leverage LLMs to label any text dataset with <5 lines of code. We’re eager for your feedback!
2023 · github.com · its alternatives →
- 11
Labelf AI▲137NLP Low code platform to train an AI with active learning
2021 · labelf.ai · its alternatives →
- 12
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Language Lego. Contribute to ayoungprogrammer/Lango development by creating an account on GitHub.
2016 · github.com · its alternatives →
- 14
Datasaur▲90Manage your entire data labeling workflow with a single tool
2020 · datasaur.ai · its alternatives →
- 15PA
Hey HN, I’m Jordan cofounder of Humanloop (YC S20) and I’m excited to show you Programmatic — an annotation tool for building large labeled datasets for NLP without manual annotation. Programmatic is like a REPL for data annotation. You: 1. Write simple rules/functions that can approximately label the data 2. Get near-instant feedback across your entire corpus 3. Iterate and improve your rules Finally, it uses a Bayesian label model [1] to convert these noisy annotations into a single, large, clean dataset, which you can then use for training machine learning models. You can…
2022 · programmatic.humanloop.com · its alternatives →
- 16
MonkeyLearn 3.0▲363Get actionable data from text with machine learning
2018 · medallia.com · its alternatives →
- 17
Manage your computer vision data labeling
2024 · labelyourdata.com · its alternatives →
- 18AN
2016 · blog.ayoungprogrammer.com · its alternatives →
- 19
Hi HN: I published part one of my free NLP course. The course is intended to help anyone who knows Python and a bit of math go from the very basics all the way to today's mainstream models and frameworks. I strive to balance theory and practice and so every module consists of detailed explanations and slides along with a Colab notebook (in most modules) putting the theory into practice. In part one, we cover text preprocessing, how to turn text into numbers, and multiple ways to classify and search text using "classical" approaches. And along the way, we'll pick up useful bits on how to use…
2022 · nlpdemystified.org · its alternatives →
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State of the art text understanding for developers
2018 · its alternatives →
- 21
Simple and customizable text classification with AI
2019 · monkeylearn.com · its alternatives →
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Intuitive Annotation Tool for Information Extraction / Named Entity Recognition using localturk / Amazon Mechanical Turk - Varal7/ieturk
2018 · github.com · its alternatives →
- 24
Learn how to build semantic search systems. From machine transition to question-answering.
2021 · pinecone.io · its alternatives →
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Ranked by how close each launch is in meaning, then by votes. Prices were read from each product’s own site when checked and can change. Refine with your own description →