Thanks guys for the ChatGPT prompting course, very useful and inspiring.
For the lamp review in the Inferring lesson I’ve updated one of the prompts in the following prompt:
What is the sentiment of the following product review,
which is delimited with triple backticks?
Give your answer as a single word, either "positive" \
or "negative".
Also capture at least 6 combination of words motivating that sentiment,
expressing them in JSON format using key
Textual_Reason_1 ... Textual_Reason_6
Finally, classify each of such reason and in the same order
to one of the following customer-centered categories:
- Value for money
- Fast delivery
- Useful product feature
- I feel understood by the company
- Easy of use
- I feel valued by the company
representing each of them in the same JSON structure
using keys Reason_1 ... Reason_6.
obtaining this very nice completion reporting both the verbatim combinations of words of the review motivating the sentiment and also their classification based on listed categories:
Sentiment: positive
{
"Textual_Reason_1": "additional storage",
"Reason_1": "Useful product feature",
"Textual_Reason_2": "not too high of a price point",
"Reason_2": "Value for money",
"Textual_Reason_3": "Got it fast",
"Reason_3": "Fast delivery",
"Textual_Reason_4": "company happily sent over a new one",
"Reason_4": "I feel understood by the company",
"Textual_Reason_5": "easy to put together",
"Reason_5": "Easy of use",
"Textual_Reason_6": "great company that cares about their customers and products",
"Reason_6": "I feel valued by the company"
}
Very impressive, I must say.