使用 Natural Language API 進行實體和情緒分析 Reviews

188326 reviews

Sham H. · Reviewed almost 2 years ago

Priyanka P. · Reviewed almost 2 years ago

Abhijeet S. · Reviewed almost 2 years ago

Arivudinambi J. · Reviewed almost 2 years ago

Ruchit P. · Reviewed almost 2 years ago

Jainam K. · Reviewed almost 2 years ago

Good

Piramanayagam U. · Reviewed almost 2 years ago

Adrian O. · Reviewed almost 2 years ago

Mukhammad Fahlevi R. · Reviewed almost 2 years ago

Yue P. · Reviewed almost 2 years ago

HaoYing G. · Reviewed almost 2 years ago

Hewi E. · Reviewed almost 2 years ago

Dina P. · Reviewed almost 2 years ago

Pardeep K. · Reviewed almost 2 years ago

This did not work

Sofia S. · Reviewed almost 2 years ago

Task 2. Make an entity analysis request The first Natural Language API method you use is analyzeEntities. With this method, the API can extract entities (like people, places, and events) from text. To try it out the API's entity analysis, use the following sentence: Joanne Rowling, who writes under the pen names J. K. Rowling and Robert Galbraith, is a British novelist and screenwriter who wrote the Harry Potter fantasy series. You build your request to the Natural Language API in the file, request.json. Use nano (a code editor) to create the file request.json: nano request.json Copied! Type or paste the following code into request.json: { "document":{ "type":"PLAIN_TEXT", "content":"Joanne Rowling, who writes under the pen names J. K. Rowling and Robert Galbraith, is a British novelist and screenwriter who wrote the Harry Potter fantasy series." }, "encodingType":"UTF8" } Copied! Press CTRL+X to exit nano, then Y to save the file, then ENTER to confirm. In the request, you're telling the Natural Language API about the text being sent. Supported type values are PLAIN_TEXT or HTML. In content, you pass the text to send to the Natural Language API for analysis. The Natural Language API also supports sending files stored in Cloud Storage for text processing. If you wanted to send a file from Cloud Storage, you would replace content with gcsContentUri and give it a value of the text file's uri in Cloud Storage. encodingType tells the API which type of text encoding to use when processing our text. The API will use this to calculate where specific entities appear in our text. Click Check my progress to verify the objective. Please create a JSON file and name it as request.json. Make an Entity Analysis Request Please create a JSON file and name it as request.json. I tried so many times but getting error for everytime

Saurabh P. · Reviewed almost 2 years ago

Thunugunta R. · Reviewed almost 2 years ago

nice jobs.

仁尾慎吾 仁. · Reviewed almost 2 years ago

仁尾慎吾 仁. · Reviewed almost 2 years ago

Luis Daniel H. · Reviewed almost 2 years ago

Karan K. · Reviewed almost 2 years ago

Phil T. · Reviewed almost 2 years ago

Gábor H. · Reviewed almost 2 years ago

:-(

Oliver D. · Reviewed almost 2 years ago

Lisa M. · Reviewed almost 2 years ago

We do not ensure the published reviews originate from consumers who have purchased or used the products. Reviews are not verified by Google.