Chat with Set

chat with set chat with set lets you analyze an entire patent dataset using natural language instead of reading patents one by one, you ask a question and the ai reads your dataset and answers for you in this section, we explain to you how this feature works and give you some best practices when using "chat with set" how it works how it works the workflow is always the same you ask a question the ai determines whether any filters need to be applied it retrieves the relevant patent data it answers your question using the patent data for each response, the ai draws on the title, abstract, claims, organization, and patent office fields of the patents in your dataset at the moment, llms have a limited context window (think of this as its memory) this means that the llm cannot query your entire dataset at once if it is too large as a rule of thumb, the llm will do the following fewer than 1,000 patent families the ai will analyze all families in the dataset more than 1,000 patent families the ai will sample and analyze up to 1,000 families the above mentioned number of families is a rule of thumb the exact number of families analyzed depends on text length domains with especially long abstracts or claims will result in fewer families being processed, and vice versa understanding which patents were considered understanding which patents were considered after every response, you can see exactly which patents the ai used to answer your question 👉 click "click here to see the patents that were considered" to expand the list this helps you verify the answer is grounded in the right data especially useful when working with large or filtered datasets hyperlinks in answers hyperlinks in answers whenever the ai mentions a specific patent in its response, it will hyperlink it directly click the link to open and explore that patent further using filters with chat with set using filters with chat with set filtering manually before you start you can apply any filters from the right hand panel before using chat with set the ai will only analyze the patents currently visible in your filtered dataset example filter by us patents + a specific organization first → chat with set will only answer based on those patents letting chat with set apply filters automatically chat with set can also apply certain filters on its own, based on how you phrase your question here's what it can control filter example prompt publication year "what are the main innovation trends in the past 3 years?" patent office "identify the main topics of invention in chinese patents in this dataset " organization "analyze all inventions by samsung and explain their innovation efforts " publication number "compare patents us 10462849 b1 and us 10383371 b2 and explain the main differences " status "analyze all pending patents and tell me about their main topics " for other filters such as similarity or keyword filters you still need to apply them manually before using chat with set each question you ask is a fresh interaction the ai re queries the dataset for every question, including follow ups this means the same question asked twice may return slightly different answers if it can be interpreted in more than one way follow up questions do not carry context forward automatically phrase each question with full context if needed saving chat with set saving chat with set you can save any chat with set conversation for future reference to save a chat click the save button in the right upper corner of the chat panel click the pen icon to rename the chat before saving a success message will confirm it's been saved click "open in folder" to jump straight to it to find saved chats click "show insights" in your workspace all saved chats, comparisons, and insights are stored here linked to the datasets each item is labeled by type so you can tell them apart at a glance you can view your saved chats by clicking on "show insights " here, you'll find all your saved chats, comparisons, and insights, conveniently stored in one place saved insights are easily distinguishable by the labels displayed beneath each item 💡 you can save multiple chats for the same dataset they'll all be accessible from that dataset's insights panel suggested use cases suggested use cases not sure where to start? here are some prompts to inspire you trend analysis trend analysis you could ask what are the latest trends in this domain? what are the main trends in this domain over the past 5 years? what are the topics being discussed in this dataset and how many inventions belong to each topic? what are the patent numbers that relate to \[your topic]? list the publication numbers in a comma separated list organization and portfolio analysis organization and portfolio analysis what are the top 3 startups in this domain? provide a summary of their most important inventions compare the portfolio's of organization x and organization y and explain the main differences to me comparing inventions and tracking development comparing inventions and tracking development what are the differences between patent x and patent y? how has this technological domain developed? compare 5 years ago with today for prompt examples, and prompting tricks, read docid\ ednbozjs3cjme3ag 9xp2