This demo is created to show the integration of Streamlit with TimelineJS. It became a timeline about the history of Natural Language…

It started with the idea for a fun pre-christmas project and with the help of Plutchik’s Wheel of Emotions and Zero-shot emotion…

A project to build a mini guide with more than 80 helpful NLP task descriptions! Structured in the format of the Periodic Table.

An overview of all demo's. Interaction with a demo beats reading and telling.

Why compute Affective Meaning? Applications can be Detecting: sentiment towards politicians, products, countries, ideas frustration of…

Sentiment Analysis can be considered a subfield of information extraction. It is used in a wide range of areas and is sometimes referred to…

Sometimes the problems encountered when trying to understand a text, or better, a corpus of documents becomes so complex that you need to…

Visualizing a network of interlinked descriptions of entities.

Plotting geocoded Named Entities on a map.

Increasing insight into text by plotting events chronological on a timeline.

Visualizing Word Embeddings is often done to inspect the embedding and experience the cohesiveness of a subset of the embedding.

Most Wordclouds seem to ignore best practices for visualizing information.

Printing text, but prettier. Text is not only characters, but also meta-info.

Presenting your NLP task results in a transparent, interactive and fancy App.

Large scale content analysis for identifying, collecting and producing information to support investigations and understand the voice of the author.

Discovering facts about entities (NER, NEL) and building a knowledge base with it.

Increasing search accuracy by adding semantic information about a piece of text to the index, in addition to keyword search.

Programming a natural and convincing chatbot dialogue for the personas of your customers, to meet your customers’ needs.

Answering questions posed by humans in a natural language, regardless of the format of the question.

Extracting semantic relationships from a text, to make a connection between entities.

Generating long sequences of words, based on long sequences of words with appropriate performance.