TAG. LABEL. CATEGORISE.

Successful data analysis relies heavily on the metadata or tags associated with your dataset, and in particular to develop supervised machine learning models you need high-quality training and evaluation data, both for the model’s initial construction and throughout its lifecycle.

But there’s no need to burden your data analysts or data scientists with this task. Whether you need simple binary classification of images, multi-level document classification, identification of themes, or the categorisation of sentiment from dense natural text, Hivemind can help.

Use cases

Entity Recognition

Entity Recognition

One of the most common ways of categorising text or documents is to tag them with the real-world objects mentioned in them, such as people, places, products or companies. Hivemind CORE can help you do that with the added precision and relevance that comes with a human-in-the-loop overlay.
READ A CLIENT CASE STUDY

Document Classification

Classifying text or documents into user-defined categories is a popular use case for Hivemind CORE — for instance when organising or triaging archives of internal research notes or other documents. This demo video explains how to set up a document classification task, using CORE.

TALK TO THE HIVEMIND TEAM
Text Annotation

Text Annotation

Speech tagging, entity recognition, chatbot training and theme identification are just some of the use cases for the text annotation feature of Hivemind CORE — where bespoke tooling allows workers to tag text interactively, and with speed and precision.
TALK TO THE HIVEMIND TEAM

Sentiment Analysis

Sentiment analysis is a popular area of NLP which often requires the creation of bespoke training datasets or, in some cases, is best left to human intuition rather than computational processes. Hivemind CORE has helped clients with projects ranging from creating training data on consumer sentiment in tweets to the assessment of corporate sentiment towards emerging themes in company announcements. This demo video explains how to create a sentiment analysis task, using CORE.
TALK TO THE HIVEMIND TEAM

TAG. LABEL. CATEGORISE.

Request a demo