An ontology describes classes and properties used for machine-computable entity descriptions. Based on my recent ChatGPT-related activity, it would only be natural to experiment with the generation of a Prompt Ontology.
Here’s a transcript used to generate a ChatGPT Prompt Ontology.
Transcript
Q: Can you generate an ontology that describes aspects of a ChatGPT prompt?
A:
Yes, I can generate an ontology that describes aspects of a ChatGPT prompt. Here is an example of what such an ontology might look like:
Ontology Name: ChatGPT Prompt Ontology
Classes:
- Prompt: Represents a prompt given to the ChatGPT model
- User: Represents a user who submits a prompt to the ChatGPT model
- Response: Represents a response generated by the ChatGPT model
- Input: Represents the input provided to the ChatGPT model
- Output: Represents the output generated by the ChatGPT model
Properties:
- hasUser: Relates a Prompt to a User who submitted it
- hasInput: Relates a Prompt to the Input provided by the User
- hasResponse: Relates a Prompt to the Response generated by the ChatGPT model
- hasOutput: Relates a Response to the Output generated by the ChatGPT model
Example of Instance:
Prompt1
- hasUser: UserA
- hasInput: “What is the capital of France?”
- hasResponse: Response1
Response1
- hasOutput: “The capital of France is Paris.”
In this ontology, the Prompt class represents a prompt given to the ChatGPT model. The User class represents a user who submitted the prompt, and the Response class represents a response generated by the ChatGPT model. The Input class represents the input provided to the ChatGPT model, and the Output class represents the output generated by the ChatGPT model.
The ontology includes properties to relate prompts to users, inputs, and responses, as well as to relate responses to outputs.
The example instance shows how the ontology can be used to represent a specific prompt, the user who submitted it, the input provided by the user, the response generated by the ChatGPT model, and the output produced by the model.
Q: RDFs rendition?
Q: Is this correct? I ask due to missing prefix declarations for namespaces used.
Q: For maximum portability, replace example.com with <#>.
Q: You are missing a description of the Ontology itself plus rdfs:isDefinedBy attributes that associate Ontology with the Classes and Properties it defines.
A:
## Turtle Start ##
@prefix rdf: <http://www.w3.org/1999/02/22-rdf-syntax-ns#> .
@prefix rdfs: <http://www.w3.org/2000/01/rdf-schema#> .
@prefix ont: <#> .
### Ontology Description ###
ont: rdf:type owl:Ontology ;
rdfs:label "ChatGPT Prompt Ontology" ;
rdfs:comment "An ontology that describes aspects of a ChatGPT prompt." .
### Class Declarations ###
ont:Prompt rdf:type rdfs:Class ;
rdfs:label "Prompt" ;
rdfs:isDefinedBy ont: .
ont:User rdf:type rdfs:Class ;
rdfs:label "User" ;
rdfs:isDefinedBy ont: .
ont:Response rdf:type rdfs:Class ;
rdfs:label "Response" ;
rdfs:isDefinedBy ont: .
ont:Input rdf:type rdfs:Class ;
rdfs:label "Input" ;
rdfs:isDefinedBy ont: .
ont:Output rdf:type rdfs:Class ;
rdfs:label "Output" ;
rdfs:isDefinedBy ont: .
### Property Declarations ###
ont:hasUser rdf:type rdf:Property ;
rdfs:label "hasUser" ;
rdfs:domain ont:Prompt ;
rdfs:range ont:User ;
rdfs:isDefinedBy ont: .
ont:hasInput rdf:type rdf:Property ;
rdfs:label "hasInput" ;
rdfs:domain ont:Prompt ;
rdfs:range ont:Input ;
rdfs:isDefinedBy ont: .
ont:hasResponse rdf:type rdf:Property ;
rdfs:label "hasResponse" ;
rdfs:domain ont:Prompt ;
rdfs:range ont:Response ;
rdfs:isDefinedBy ont: .
ont:hasOutput rdf:type rdf:Property ;
rdfs:label "hasOutput" ;
rdfs:domain ont:Response ;
rdfs:range ont:Output ;
rdfs:isDefinedBy ont: .
### Example Instance ###
ont:Prompt1 rdf:type ont:Prompt ;
ont:hasUser ont:UserA ;
ont:hasInput "What is the capital of France?" ;
ont:hasResponse ont:Response1 .
ont:Response1 rdf:type ont:Response ;
ont:hasOutput "The capital of France is Paris." .
## Turtle End ##
Nanotation
The use of ## Turtle Start ## and ## Turtle End ## comment markers around the RDF-Turtle based Prompt Ontology me to store lift and store the RDF to a Knowledge Graph stored in SPARQL-compliant database management system (DBMS) of my choosing. This is made possible by the OpenLink Structured Data Sniffer (OSDS) Browser Extension.
Screenshots
Screenshot 1
Screenshot 2
Screenshot 3
OpenLink Structured Data Sniffer Availability Options
- Google Chrome Store for Chromium-based Browsers
- Mozilla Store for Firefox
- Mac App Store for Safari
- Github Open Source Repository