Written by Weiru Chen, Dean Hathout, David Zheng, Tyler Yoo.We would like to thank Gabriel Altay and Georg Kucsko at Kensho for their graciousness in sharing their time and resources with us throughout this project. Finally, we thank Chris Tanner of IACS at Harvard for his invaluable guidance to our group and for his leadership throughout the Capstone experience.
Written by Weiru Chen, Dean Hathout, David Zheng, Tyler Yoo
_Code can be found on our [Github_](https://github.com/iacs-capstone-kensho/named-entity-linking)
We would like to thank Gabriel Altay and Georg Kucsko at [Kensho_](https://www.kensho.com/) for their graciousness in sharing their time and resources with us throughout this project._
Finally, we thank Chris Tanner of [IACS_](https://iacs.seas.harvard.edu/) at Harvard for his invaluable guidance to our group and for his leadership throughout the [Capstone_](https://www.capstone.iacs.seas.harvard.edu/)_ experience._
Named Entity Linking, also known as Named Entity Disambiguation (NED) is the task of uniquely identifying entities (such as individuals, locations, companies, or historical events) mentioned in text. To give a canonical example, if given the sentence “Paris is the capital of France,” we want to be able to discern if the word ‘Paris’ is referring to the French capital, some other city, Paris Hilton, or many other possibilities, shown below.
Figure 1: Wikipedia’s “Paris” Disambiguation Page
Along with Named Entity Recognition (NER) — the process of actually identifying mentions of such entities in text — NED is one of the most foundational tasks in Natural Language Processing (NLP); being able to identify the specific things a text is talking about is essential for countless NLP applications, including general text analysis, semantic search systems, building chatbots, etc.
Set up the Roku device and perform the Roku activation process via Roku.com/link and stream your favorite channels and contents.
Using Spark NLP with Jupyter notebook for natural language processing in Docker environment. As described in , Docker is a tool that allows us to easily deploy applications (e.g., Spark NLP) in a sandbox (called container) to run on any Docker supported host operating system (i.e., Mac).
Using ScispaCy for Named-Entity Recognition - A step-by-step tutorial for extracting data from biomedical literature
Fine-tune BERT model for NER task utilizing HuggingFace Trainer class.In this article, I’m making the assumption that the readers already have background information on the following subjects: Named Entity Recognition (NER). Bidirectional Encoder Representations from Transformers (BERT). HuggingFace (transformers) Python library.
Let’s make relationships between entities with Entity Framework Core easy with Code First approach