
Roadmap: https://miro.com/app/board/uXjVKcwQ58A=/
??????: used for summarising an article.
To summarize the article, Google uses key points from facts, not opinions and relative probability. In Google Documents there is always a summary creator engine that uses the same methodology (using key points for summarization)
In definitional articles and questions always go with absolute fact or create consensus in your document and don't create conflicting declarations. Even a single adjective or adverb used in a destructive way can eliminate the answer according to the search engine.
?????: is used to augment the specific context even if it's not stated there.
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"We paid twenty__ at the Buckingham Palace gift shop."
Here we don't have a currency name but Buckingham Palace is located in the United Kingdom and the currency of the United Kingdom is ponds so this should be in ponds. This kind of algorithms are expensive. That's why give everything explicitly by definite answers mentioning every attribute.
??? ???????: Donald Trump is the 47th president of the USA.
?????????????? ?????? ??????????: this is important that we do with ChatGPT. We learned about query path in recent posts, search "Turkey Recipes" and then search for "Carving" The definition of carving will be shown. Now again search for "Turkey Recipes" and then search for "Carving" since there is a query path from Recipes to Carving "Carving to Turkey" appears here.
That's why give query meaning according to user behavior as much as possible.
?????: Every question has been connected to another question. What we do in content briefs is generate a question match its answer and move on to the next question. Usually, questions in the headings are representative questions and have supportive questions for evidence.
???: according to the central entity and source context semantic content network you're creating will be changing.
????: Used to find the overall relevance. learn relationships between the next sentence.
Sentence A= " The Man went to the store"
Sentence B=" He bought a gallon of milk"(IsNextSentence)
Sentence A= " The Man went to the store"
Sentence B= "Penguins are flightless" (NotNextSentence)
Tells that proceeding sentence is matching the context of first sentence or not.
????:
Used for verification and accuracy checking for the declarations in the documents. Find facts in your document that exist in the knowledge base or not.
????: it uses all the possible explanations for understanding the efficiency of the Language model
????: Generate text faster while preserving output quality.
????-?: performs visual tasks, such as describing images, detecting objects, or classifying scenes, and is also proficient at language tasks.
Common phrases like "health benefits of hot water" are generic and widely used, so they don’t make your content stand out much. However, if you incorporate unique n-grams like "drinking hot water after dinner" or "drinking hot water during winter," Give me some Unique N-Grams for "Niche/Heading"
"Use factual sentence structures. (X is known for Y → X does Y)" Koray
Use research and university studies to prove the point. (X provides Y → According to X University research from Z Department, on C Date, the P provides Y)
Official Instructions from Koray
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