使用知识图谱，自然语言处理，卷积神经网络等技术，基于python语言，设计了一个数控领域故障诊断专家系统

AlpacaTag: An Active Learning-based Crowd Annotation Framework for Sequence Tagging (ACL 2019 Demo)

Named Entity Recognition & Relation Extraction 实体命名识别与关系分类

Notebooks for teaching Named Entity Recognition at the Cultural Heritage Data School, run by Cambridge Digital Humanities

Source code for the Medium article "Extracting the author of news stories with DOM-based segmentation and BERT"

An NER tool for ancient place names based on Pleiades and Spacy.

LSTM based model for Named Entity Recognition Task using pytorch and GloVe embeddings

Undergraduate graduation project (Entity Linking System in Web Tables with Multiple Linked Knowledge Bases) at SEU.

This project is to develop a named entity recognition (NER) model to identity medical entities such as diseases, symptoms, treatments in the unstructured medical text written in natural language.

🚀SpAnnor annotator for Named Entity Recognition easy to use tool. The annotator allows users to quickly assign custom labels to one or more entities in the text. Easy to setup for Data Training for SpaCy 🔥.

Named Entity Extraction in Wikipedia Pages

We bridge the AI gap for you

A python project for creating an openKG for Game of Thrones.

DFLER: Drone Flight Log Entity Recognizer to Support Forensic Investigation on Drone Device

Development of a starter dataset for Security Force Monitor NLP projects

An application for accumulating all disaster updates in one forum, parsing them and manipulating the data so that only accurate information reaches the people. Features include SOS, mapping, video surveillance and many more features to come.

A GUI for training MITIE NER models

🚀SpAnnor annotator for Named Entity Recognition easy to use tool. The annotator allows users to quickly assign custom labels to one or more entities in the text. Easy to setup for Data Training for SpaCy 🔥.

Jargon is a Named-Entity-Recognition approach to automating the analysis of terms-and-conditions or privacy-policies.

My solutions for excercises in topics of semantic data. If you found some of my code useful, please leave a star :)