Re: Demo: Query Language Cheatsheet Generation using ChatGPT 3.5

Hi Adasal,

On 5/2/23 8:32 AM, adasal wrote:
> Hi Kingsley,
>
> This is brilliant.
> You might have seen my last email about GPT 3.5 compared to 4 going 
> over your last post?


Yes, I posted a reply.


>
> I had thought that they would be good for producing SPARQL, though.


That's the next step. I wanted to start with very basic examples that 
showcase the most basic aspects of hyperlinks functioning as entity 
names that manifest a giant global entity relationship graph (a/k/a a 
Semantic Web).


>
> You have shown my assumption to be correct.
>
> Do you have any thoughts about producing the whole life cycle?


I am a little unclear about what you mean by "whole life cycle?" question.


>
> I'm a non-technical outsider.
> My understanding is that linked data, in terms of URLs, 
> guarantees origin of documents which it retrieves according to a 
> possibly complex logical request.


Yes.

>
> But the original documents have to be annotated in the first place.


They have to describe whatever the hyperlink denotes.


>
> So, for instance, Wikidata ".. acts as central storage for the 
> *structured data* of its Wikimedia sister projects including 
> Wikipedia, Wikivoyage, Wiktionary, Wikisource, and others."
>
> There is a life cycle from Wikipedia to a representation in Wikidata.


Yes.


>
> How is this accomplished and could eg ChatGPT, help?


ChatGPT simply offers tools for productivity understanding the end 
product of following certain "best practices" for structured data 
representation using entity relationship graphs constructed using 
hyperlinks.

Wikidata has an annotation system to drives how its data is derived from 
Wikipedia content en route to publication using Linked Data principles, 
that's it :)


Kingsley

>
>
> Adam Saltiel
>
>
>
> On Mon, May 1, 2023 at 10:13 PM Kingsley Idehen 
> <kidehen@openlinksw.com> wrote:
>
>     All,
>
>     ChatGPT 3.5 is less capable that 4.0, but much faster. Here’s a
>     transcript demonstrating the creation of SQL and SPARQL
>     cheatsheets – that I just generated (whimsically).
>
>
>       Transcript
>
>     Q: Make a simple SQL Cheatsheet.
>     Q: Redo, but using a Table for enhanced presentation.
>     Q: Redo the SQL cheatsheet using a Markdown Table in a code-block.
>     A:
>     Sure, here is the SQL cheatsheet presented in a markdown table
>     inside a code block:
>
>     Command  Description
>     SELECT  Retrieves data from one or more tables
>     |SELECT column1, column2, ... FROM table_name;|  
>     DISTINCT  Retrieves unique values
>     |SELECT DISTINCT column_name FROM table_name;|  
>     WHERE  Filters records based on a condition
>     |SELECT column1, column2, ... FROM table_name WHERE condition;|  
>     AND/OR  Combines multiple conditions
>     |SELECT column1, column2, ... FROM table_name WHERE condition1
>     AND/OR condition2;|  
>     ORDER BY  Sorts the result set
>     |SELECT column1, column2, ... FROM table_name ORDER BY column_name
>     ASC/DESC;|  
>     LIMIT  Limits the number of results returned
>     |SELECT column1, column2, ... FROM table_name LIMIT number_of_rows;|  
>     JOIN  Combines rows from two or more tables based on a related
>     column between them
>     |SELECT column1, column2, ... FROM table1 JOIN table2 ON
>     table1.column_name = table2.column_name;|  
>     GROUP BY  Groups rows based on a column
>     |SELECT column1, COUNT(column2) FROM table_name GROUP BY column1;|  
>     HAVING  Filters groups based on a condition
>     |SELECT column1, COUNT(column2) FROM table_name GROUP BY column1
>     HAVING COUNT(column2) > value;|  
>     INSERT INTO  Inserts new records into a table
>     |INSERT INTO table_name (column1, column2, ...) VALUES (value1,
>     value2, ...);|  
>     UPDATE  Modifies existing records in a table
>     |UPDATE table_name SET column1 = value1, column2 = value2, ...
>     WHERE condition;|  
>     DELETE FROM  Deletes records from a table
>     |DELETE FROM table_name WHERE condition;|  
>
>     I hope this presentation is helpful and easy to read.
>
>     Q: Redo, with an examples column using Northwind
>     A:
>     Sure, here is an updated SQL cheatsheet presented in a markdown
>     table inside a code block with an additional column for actual
>     usage examples based on the Northwind database schema:
>
>     Command  Description  Example
>     SELECT  Retrieves data from one or more tables  |SELECT
>     ProductName, UnitPrice FROM Products;|
>     DISTINCT  Retrieves unique values  |SELECT DISTINCT CategoryID
>     FROM Products;|
>     WHERE  Filters records based on a condition  |SELECT ProductName,
>     UnitPrice FROM Products WHERE UnitPrice > 20;|
>     AND/OR  Combines multiple conditions  |SELECT ProductName,
>     UnitPrice FROM Products WHERE CategoryID = 1 AND Discontinued = 0;|
>     ORDER BY  Sorts the result set  |SELECT ProductName, UnitPrice
>     FROM Products ORDER BY UnitPrice DESC;|
>     LIMIT  Limits the number of results returned  |SELECT ProductName,
>     UnitPrice FROM Products LIMIT 10;|
>     JOIN  Combines rows from two or more tables based on a related
>     column between them  |SELECT Products.ProductName,
>     Suppliers.CompanyName FROM Products JOIN Suppliers ON
>     Products.SupplierID = Suppliers.SupplierID;|
>     GROUP BY  Groups rows based on a column  |SELECT CategoryID,
>     COUNT(*) FROM Products GROUP BY CategoryID;|
>     HAVING  Filters groups based on a condition  |SELECT CategoryID,
>     COUNT(*) FROM Products GROUP BY CategoryID HAVING COUNT(*) > 5;|
>     INSERT INTO  Inserts new records into a table  |INSERT INTO
>     Products (ProductName, UnitPrice) VALUES ('Chai', 18.00);|
>     UPDATE  Modifies existing records in a table  |UPDATE Products SET
>     UnitPrice = 20 WHERE ProductID = 1;|
>     DELETE FROM  Deletes records from a table  |DELETE FROM Products
>     WHERE ProductID = 1;|
>     I hope this updated version of the SQL cheatsheet with examples
>     based on the Northwind database schema is helpful for you to
>     practice with.  
>      
>
>     Q: Repeat, for SPARQL using DBpedia for examples.
>     A:
>     Sure, here is the SPARQL cheatsheet presented in a markdown table
>     inside a code block with an additional column for actual usage
>     examples using DBpedia for the examples:
>
>     Command  Description  Example
>     SELECT  Retrieves data from one or more RDF graphs  |SELECT
>     ?person ?birthdate WHERE { ?person dbo:birthDate ?birthdate }
>     LIMIT 10|
>     DISTINCT  Retrieves unique values  |SELECT DISTINCT ?category
>     WHERE { ?product dcterms:subject ?category }|
>     WHERE  Filters RDF triples based on a condition  |SELECT ?film
>     WHERE { ?film rdf:type dbo:Film . ?film dbo:starring
>     dbr:Harrison_Ford . }|
>     FILTER  Filters query results based on a condition  |SELECT ?film
>     WHERE { ?film rdf:type dbo:Film . ?film dbo:budget ?budget .
>     FILTER(?budget > 100000000) }|
>     UNION  Combines the results of two or more queries  |SELECT ?name
>     WHERE { { ?person foaf:name ?name } UNION { ?organization
>     foaf:name ?name } }|
>     OPTIONAL  Retrieves optional RDF triples  |SELECT ?book ?author
>     WHERE { ?book rdf:type dbo:Book . OPTIONAL { ?book dbo:author
>     ?author } }|
>     ORDER BY  Sorts the query results  |SELECT ?person ?birthdate
>     WHERE { ?person dbo:birthDate ?birthdate } ORDER BY
>     DESC(?birthdate) LIMIT 10|
>     LIMIT  Limits the number of results returned  |SELECT ?person
>     WHERE { ?person rdf:type dbo:Person } LIMIT 10|
>     GROUP BY  Groups query results based on a variable  |SELECT
>     ?category (COUNT(?product) AS ?count) WHERE { ?product
>     dcterms:subject ?category } GROUP BY ?category|
>     HAVING  Filters groups based on a condition  |SELECT ?category
>     (COUNT(?product) AS ?count) WHERE { ?product dcterms:subject
>     ?category } GROUP BY ?category HAVING (COUNT(?product) > 100)|
>
>     Note: The examples above assume the use of the DBpedia SPARQL
>     endpoint (https://dbpedia.org/sparql). If you want to test these
>     queries, you can use the DBpedia SPARQL endpoint or install your
>     own copy of DBpedia.
>
>     Q: Redo for SPARQL including DESCRIBE, CONSTRUCT, COPY, and MOVE
>     commands
>     A:
>     Sure, here is the SPARQL cheatsheet presented in a markdown table
>     inside a code block with additional commands and actual usage
>     examples using DBpedia for the examples:
>
>     Command  Description  Example
>     SELECT  Retrieves data from one or more RDF graphs  |SELECT
>     ?person ?birthdate WHERE { ?person dbo:birthDate ?birthdate }
>     LIMIT 10|
>     DISTINCT  Retrieves unique values  |SELECT DISTINCT ?category
>     WHERE { ?product dcterms:subject ?category }|
>     WHERE  Filters RDF triples based on a condition  |SELECT ?film
>     WHERE { ?film rdf:type dbo:Film . ?film dbo:starring
>     dbr:Harrison_Ford . }|
>     FILTER  Filters query results based on a condition  |SELECT ?film
>     WHERE { ?film rdf:type dbo:Film . ?film dbo:budget ?budget .
>     FILTER(?budget > 100000000) }|
>     UNION  Combines the results of two or more queries  |SELECT ?name
>     WHERE { { ?person foaf:name ?name } UNION { ?organization
>     foaf:name ?name } }|
>     OPTIONAL  Retrieves optional RDF triples  |SELECT ?book ?author
>     WHERE { ?book rdf:type dbo:Book . OPTIONAL { ?book dbo:author
>     ?author } }|
>     ORDER BY  Sorts the query results  |SELECT ?person ?birthdate
>     WHERE { ?person dbo:birthDate ?birthdate } ORDER BY
>     DESC(?birthdate) LIMIT 10|
>     LIMIT  Limits the number of results returned  |SELECT ?person
>     WHERE { ?person rdf:type dbo:Person } LIMIT 10|
>     GROUP BY  Groups query results based on a variable  |SELECT
>     ?category (COUNT(?product) AS ?count) WHERE { ?product
>     dcterms:subject ?category } GROUP BY ?category|
>     HAVING  Filters groups based on a condition  |SELECT ?category
>     (COUNT(?product) AS ?count) WHERE { ?product dcterms:subject
>     ?category } GROUP BY ?category HAVING (COUNT(?product) > 100)|
>     DESCRIBE  Retrieves RDF triples that describe a resource
>     |DESCRIBE <http://dbpedia.org/resource/Barack_Obama>
>     <http://dbpedia.org/resource/Barack_Obama>|
>     CONSTRUCT  Generates an RDF graph based on a query pattern
>     |CONSTRUCT { ?book dbo:author ?author } WHERE { ?book rdf:type
>     dbo:Book . ?book dbo:author ?author }|
>     COPY  Copies a named graph from one location to another  |COPY
>     <http://example.org/graph1> <http://example.org/graph1> TO
>     <http://example.org/graph2> <http://example.org/graph2>|
>     MOVE  Moves a named graph from one location to another  |MOVE
>     <http://example.org/graph1> <http://example.org/graph1> TO
>     <http://example.org/graph2> <http://example.org/graph2>|
>
>     Note: The examples above assume the use of the DBpedia SPARQL
>     endpoint (https://dbpedia.org/sparql). If you want to test these
>     queries, you can use the DBpedia SPARQL endpoint or install your
>     own copy of DBpedia.
>
>     ​
>

-- 
Regards,

Kingsley Idehen 
Founder & CEO
OpenLink Software
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