ChatGPT is notorious for producing content in the blink of an eye and has proven to be a huge time saver.
For content already written, ChatGPT can also save us time by helping us digest long torturous texts.
It can summarize books, movies, plays, articles, and many more. With ChatGPT, it’s like having a Cliff’s Notes…ON EVERYTHING!
Sometimes, you can ask ChatGPT to summarize famous works without pasting in any additional text, since ChatGPT knows the works so well. For example, you can ask it to summarize “Romeo & Juliet” by act. So, instead of slogging through the 24,000 words of the play, you can get the gist in 300 or less.
Give me an act-by-act summary of Romeo and Juliet
Sure, here's an act-by-act summary of "Romeo and Juliet":
Act 1: The play begins with a street brawl between the servants of the Montague and Capulet families in Verona, Italy. The Prince of Verona intervenes and warns the families that any further fighting will result in death. Romeo, a young Montague, is in love with Rosaline, but she does not return his affections. Romeo and his friends decide to attend a Capulet party, where he meets and falls in love with Juliet, the daughter of his family's enemies.
Act 2: Romeo sneaks into the Capulet's orchard to see Juliet and profess his love to her. They decide to marry in secret with the help of Friar Laurence. Juliet's Nurse is aware of the plan and helps to arrange the marriage.
Act 3: Tybalt, Juliet's cousin, challenges Romeo to a duel, but Romeo refuses to fight. Romeo's friend, Mercutio, fights Tybalt and is killed. In a fit of rage, Romeo kills Tybalt and is banished from Verona by the Prince. Juliet is devastated by Romeo's banishment.
Although you could instead look up a summary, ChatGPT can tailor the content to your needs. Maybe you really like Football, so you could ask ChatGPT:
Give me a 100-word summary of ‘Romeo and Juliet’ in American football terms.
You can ask ChatGPT to summarize or create an outline of the text and TL;DR the whole thing. All you have to do is copy and paste the specific text into the prompt. (You can include up to 2,500 words. If the work is longer than that, you will have to break it into chunks.)
Ask for a simplified summary of the chosen text by writing:
Summarize this for me like I'm 5 years old: [PASTE TEXT HERE]
This one is a summary “for a 5-year-old” from a section of Wikipedia’s entry on “quantum entanglement”:
Summarize this for me like I'm 5 years old:
Quantum entanglement is the phenomenon of a group of particles being generated, interacting, or sharing spatial proximity in such a way that the quantum state of each particle of the group cannot be described independently of the state of the others, including when the particles are separated by a large distance. The topic of quantum entanglement is at the heart of the disparity between classical and quantum physics: entanglement is a primary feature of quantum mechanics not present in classical mechanics.
Quantum entanglement is a very strange thing that happens to very tiny things called particles. When two particles are "entangled," it means that they are connected in a special way, even if they are far apart. Scientists have found that if they measure something about one entangled particle, it can tell them something about the other one, even if they are very far apart. This is really weird and it took a long time for scientists to understand it. They used to think it was impossible, but now they know it's real! Even though it seems like this could be used to send messages really fast, it can't. But scientists are still studying it to see what they can learn from it.
In addition to summaries, you can also ask ChatGPT to write outlines for blocks of text. Sometimes it’s better to have an outline so that you can see the thread or framework of the whole article. You also just need to copy and paste the text you want outlined into your prompt.
Write an outline for this text: [PASTE TEXT HERE]
The following is ChatGPT’s outline on the Wikipedia page on “rope,” specifically on the history of rope:
I. Introduction
- The use of ropes dates back to prehistoric times - The earliest ropes were naturally occurring lengths of plant fibre - The evolution of rope-making involved the twisting and braiding of plant fibres together - The earliest evidence of suspected rope was a fragment of three-ply cord found in a Neanderthal siteII. Historical development of rope-making
- A 40,000-year-old tool found in Germany was identified in 2020 as a tool for making rope - The ancient Egyptians developed special tools to make rope around 4000-3500 BC - Other ancient civilisations used ropes made from various materials such as flax, grass, and animal hair - Rope-making spread throughout Asia, India, and Europe over the next several thousand years - From the Middle Ages until the 18th century, ropes were constructed in ropewalks, where strands of rope were laid out and then twisted together to form the rope -Domenico Fontana erected the 327-ton obelisk on Rome's Saint Peter's Square in 1586 with the help of 900 men, 75 horses, and countless pulleys and meters of ropeIII. Modern developments in rope-making
- Synthetic fibres like nylon and polypropylene have become increasingly popular since the 1950s - Nylon was first introduced into fiber ropes during World War II, and was used to make small braided parachute cords and three-strand tow ropes for glidersIV. Conclusion
- While synthetic fibres have largely replaced natural fibres in modern rope-making, the evolution of rope-making from prehistoric times to the present day has allowed for the creation of stronger and more durable ropes, which have played a crucial role in human history.We’ve just covered some of the very basics of using ChatGPT to handle long texts. There are many more ways to use ChatGPT to summarize and outline texts!
By languagenoodle.
Sander Schulhoff is the Founder of Learn Prompting and an ML Researcher at the University of Maryland. He created the first open-source Prompt Engineering guide, reaching 3M+ people and teaching them to use tools like ChatGPT. Sander also led a team behind Prompt Report, the most comprehensive study of prompting ever done, co-authored with researchers from the University of Maryland, OpenAI, Microsoft, Google, Princeton, Stanford, and other leading institutions. This 76-page survey analyzed 1,500+ academic papers and covered 200+ prompting techniques.