3 Repos
Tools for visually highlighting identified semantic entities within text for analysis.
Distinct from Entity Modeling: Focuses on UI highlighting of NLP results rather than database entity modeling.
Explore 3 awesome GitHub repositories matching user interface & experience · Entity Visualizations. Refine with filters or upvote what's useful.
Flair is a natural language processing framework for training and applying models for sequence labeling and text classification. It provides a system for generating word embeddings and identifying semantic entities within text. The framework includes a dedicated system for zero and few-shot learning, enabling text classification and entity extraction using minimal training examples by leveraging pre-trained knowledge. Its capabilities cover named entity recognition, sentiment analysis, and the training of specialized models using custom datasets. It also includes tooling for the visual highl
Displays identified text entities with visual highlights to simplify manual review and analysis of model results.
ActiveLabel.swift ist eine Rich-Text-Parsing-Bibliothek und ein interaktives Text-Label für iOS. Es fungiert als Ersatz für Standard-Labels, identifiziert spezifische Textmuster innerhalb von Strings und wendet unterschiedliche visuelle Stile auf erkannte Entitäten an. Das Projekt ermöglicht die Erkennung und Hervorhebung von Hashtags, Mentions und URLs mittels eines benutzerdefinierten Text-Recognizers für reguläre Ausdrücke. Es erlaubt die Definition projektspezifischer Textmuster und verwendet prädikatbasierte Filterung, um zu bestimmen, ob erkannte Entitäten hervorgehoben oder ignoriert werden sollen. Das System verwaltet Benutzerinteraktionen durch Entity-Tap-Handling, das Callback-Funktionen auslöst, wenn Benutzer mit erkannten Elementen interagieren. Es enthält zudem Utilities für URL-Management, wie das Kürzen langer Webadressen, um die Layout-Konsistenz zu wahren.
Visually highlights identified semantic entities like hashtags and links within text for user interaction.
Spark NLP is a toolkit for scalable text analysis and machine learning built on the Apache Spark distributed computing framework. It provides a multimodal machine learning framework and a distributed pipeline system for sequencing annotators to process large-scale linguistic data. The library includes a transformer text processor for generating contextual vector embeddings and a dedicated inference engine for managing large language models. The project distinguishes itself through its ability to process heterogeneous data types, including text, audio, and images, within a unified vision-langu
Visually highlights normalized medical terminology codes and descriptions on top of identified entities.