ChatGPT : pour un jargon scientifique plus accessible grâce à l’IA
Laboratório em Humanidades Digitais | UMinho
Journée d’études Mots/Machines # 5
Université de Bretagne Occidentale
Brest | 17 mars 2023
Outline
Exploring terminology
with ChatGPT
Can help automating repetitive tasks
Organizing and presenting information in various formats
Source of structured information like examples and definitions
Adapting information to different tones and complexity levels
Source of feedback for written text
Source of insights on complex problems and hypotheses validation
ChatGPT Drawbacks
Accuracy
Generates wrong and artificial information, including non-existent references (Hallucination)
Bias
Bias in the training data will cause bias in the model
Understanding
The model doesn’t have a true understanding
Creativity
Creativity is limited
by patterns
in the training data
Workflow
Extract > Define > Visualize
MULTIMODALITY
> use of more than one mode of communication in a text to create meaning
Building mind maps with
ChatGPT + Draw.io
Mind maps for structuring information
Mind map:
Arranges information in a hierarchical structure, showcasing how each piece of information is related to the overall concept.
It presents a clear picture of the relationships among different components of the information, making it easy to comprehend and analyze
Source: https://en.wikipedia.org/wiki/File:Cubital_Fossa2.png
1- Getting structured text
2- Getting PlantUML code
Prompt:
write mind map in PlantUML format
central topic: ChatGPT
first level: list hierarchy first level
second level: split elements list hierarchy second level
must have domains and subdomains branching out from central topic
2- Getting PlantUML code
Output:
@startmindmap
* ChatGPT
** Features
*** Language generation
*** Learning from data
*** Fine-tuning for domains
** Limitations
*** Bias and context sensitivity
*** Limited understanding of non-textual cues
*** High computational requirements
** Applications
*** Customer service
*** Personalized assistants
*** Language learning tools
@endmindmap
2- Getting mind map
2- Getting mind map
2- Getting mind map
Text mining | Outputs
Creating videos with Simpleshow
2- Getting PlantUML code
Prompt:
write the script for a 30 seconds video using the text from the mind map from your last answer
2- Script
Output:
2- Making the video
Prompt:
write the script for a 30 seconds video using the text from the mind map from your last answer
Text mining | Outputs
https://videos.simpleshow.com/JSZ33Ha2fq
Share your work in our Padlet!
https://bityli.com/h6bYyE
Workflow
Extract > Define > Visualize
KEYWORD EXTRACTION
Prompt:
List all technical terms from the text “text”.
KEYWORD EXTRACTION
DEFINITION
Prompt:
write a glossary using all the terms from your last answer. Each term must have a definition, example use in context, synonym list, related terms list, in this order. Example must be different from original text.
DEFINITION
VISUALIZATION
Prompt:
Given a text extrapolate as many relationships as possible from it. Every node has an color (in hex). Every edge has a to and from with node and must have a label. Edges are directed, so the order of the from and to is important. Write Graphviz code do build a knowledge graph diagram. text = "text"
VISUALISATION
Links
Thank you!
Francisco Lopes
franciscolopesdacunha@gmail.com
Sílvia Araújo
saraujo@elach.uminho.pt
Micaela Aguiar
maguiar60@gmail.com