VenBioGen: Difference between revisions

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== Motivation ==
== Motivation ==
Sneak 100
This project is an interesting exploration into the intersection between Humanities and Natural Language Processing (NLP) applied to text generation.
 
By generating fictional biographies of Venetians up to and including the 19th century, this model allows, on one hand, us to evaluate the current state, progress and limitation of text generation. Even more worthwhile, the question of whether underlying historical tendencies - most commonly under the form of international or inter-familial relationships - are learnt by the model can be explored.


== Project Plan and Milestones ==
== Project Plan and Milestones ==

Revision as of 12:40, 19 November 2020

Introduction

In this project, we use generative models to come up with creative biographies of Venetian people that existed before the 20th century. Our motivation was originally to observe how such a model would pick up on underlying relationships between Venetian actors in old centuries as well as their relationships with people in the rest of the world. These underlying relationships might or might not come to light in every generated biography, but we can be sure that the model has the potential to offer fresh perspectives on historical tendencies.

Motivation

This project is an interesting exploration into the intersection between Humanities and Natural Language Processing (NLP) applied to text generation.

By generating fictional biographies of Venetians up to and including the 19th century, this model allows, on one hand, us to evaluate the current state, progress and limitation of text generation. Even more worthwhile, the question of whether underlying historical tendencies - most commonly under the form of international or inter-familial relationships - are learnt by the model can be explored.

Project Plan and Milestones

Milestone 1 (up to 1 October)

  • Brainstorm project ideas
  • Prepare presentation to present two ideas for the project

Milestone 2 (up to 14 November)

  • Finalize project planning
  • Build generative model
    • Finetune GPT-II model
    • Finetune Bert
  • Examine generated biographies and think about further improvements

Milestone 3 (up to 20 November)

  • Create frontend for interface
  • Create backend for interface
  • Figure our API

Milestone 4 (up to 5 December)

  • Add post-processing date adjustment module
  • Add historical realism enhancement module

Milestone 5 (up to 11 December)

  • Evaluate our model
  • Review code
  • Finalize documentation
  • Finalize report

Interface

Generative module

Data processing pipeline

Text generation

GPT2

BERT

Enhancements module

Date adjustments

Adding historical realism

Quality assessment

Results