Get all entities from {{googleapi:Enter your keyword here,Enter your Google NLP API key}}

<<Step1>> {{tab}} <<Step2>> Extract all the entities from the received parts. Then provide a list of synonyms for each of those entities. Then list the above entities in a table. In the first column, list the entities. In the second column, list related concepts to each entity. Then list entities which are not mentioned in the text, but where you think it would make sense to add them in the text, given the goal that I want to optimize this text with semantical SEO in mind.

<<Step1>> {{tab}} <<Step2>> Extract all keywords and entities from the received parts. Keywords can be 1-grams, 2-grams, 3-grams or 4-grams. Then create a table in markdown format. Enter all 1-grams into the first column of the table. Then enter all 2-grams into the second column of the table. Fill the 3rd column with 3-grams and the 4th column with 4-grams. Then make another markdown table and enter all found entities there. Output format: markdown

Act as an SEO expert who specialized in entities, semantic SEO and natural language processing. You are very knowledgeable in the concept of Entity-Attribute-Value. You read all patents which had been published by Google, specifically the patents that mention entities and deal with the contextual meaning of search terms. You also studied the work of Bill Slawski. TOPIC = "{{Enter topic}}" Create a table in markdown format with 6 columns. Column 1 "Verbs": “Provide a comprehensive list of the most common verbs associated with the topic. Cluster the list and nest associated verbs. Only add verbs.” Column 2 "Nouns": "Provide a comprehensive list of the most common nouns associated with the topic. Cluster the list and nest associated nouns. Only add nouns." Column 3 "Adjectives": "Provide a comprehensive list of the most common adjectives associated with the topic. Cluster the list and nest associated adjectives. Only add adjectives." Column 4 "Adverbs": "Provide a comprehensive list of the most common adverbs associated with the topic. Cluster the list and nest associated adverbs. Only add adverbs." Column 5 "Predicates": "Provide a comprehensive list of the most common predicates associated with the topic. Only add predicates." Column 6 "Attributes": "Provide a comprehensive list of attributes associated with the topic. Only add attributes." Only create the table and nothing else. Don't give additional explanations.

You are a recruiter trying to attract top talent. You came across this LinkedIn profile "{{url:}}". You have to pitch your job offer and you can't write more than 500 characters. Your message should include: The name of the company they're currently working for which is {{name of your company}}. Praise for their areas of expertise Why they would be a good fit as a "{{job you have to offer}}" The message should be exciting and make them want to learn more about the job opportunity.

You are an assistant helping to write an essay. Use this format, replacing text in brackets with the result. Do not include the brackets in the output: Essay in [Identified language of the topic]: # [Essay title] [Introduction paragraph] ## [Name of topic 1] [Paragraph about topic 1] ## [Name of topic 2] [Paragraph about topic 2] ## [Name of topic 3] [Paragraph about topic 3] ## ['Conclusion', in the identified language of the topic] [Conclusion paragraph]

You are an assistant helping to draft a personalized recruiting email. Use this format, replacing text in brackets with the result. Do not include the brackets in the output: Recruiting email in [Identified language of the notes]: # [Recruiting email title] [Recruiting email subject] [Recruiting email body]

<<Step1>> PAA = {{paa:topic}} <<Step2>> Use PAA to create 20 people also ask questions. Then add the 4 people-also-ask questions from PAA to the list: