- 概要
- Act! 365
- ActiveCampaign
- Adobe Acrobat Sign
- Adobe PDF Services
- Amazon Bedrock
- Amazon Connect
- Amazon Polly
- Amazon SES
- Amazon Transcribe
- Anthropic Claude
- Asana
- AWeber
- Azure AI Document Intelligence
- Azure Maps
- BambooHR
- Box
- Brevo
- Calendly
- Campaign Monitor
- Cisco Webex Teams
- Citrix ShareFile
- Clearbit
- Confluence Cloud
- Constant Contact
- Coupa
- Customer.io
- Datadog
- Deputy
- Discord - プレビュー
- DocuSign
- Drip
- Dropbox
- Dropbox Business
- Egnyte
- Epic FHIR R4 - プレビュー
- Eventbrite
- Exchangerates
- Expensify
- Facebook
- Freshbooks
- Freshdesk
- FreshService
- Getresponse
- GitHub
- Google マップ
- Google Speech-to-Text
- Google Text-to-Speech
- Google Vertex
- Google Vision - プレビュー
- GoToWebinar
- Greenhouse
- Hootsuite
- HTTP Webhook
- HubSpot CRM
- Hubspot Marketing
- iContact
- Insightly CRM
- Intercom
- Jira
- Keap
- Klaviyo
- LinkedIn
- Mailchimp
- Mailjet
- MailerLite
- Mailgun
- Marketo
- Microsoft Azure OpenAI
- Microsoft Dynamics CRM
- Microsoft Sentiment
- Microsoft Teams
- リリース ノート
- Microsoft Teams アクティビティ パッケージについて
- プロジェクトの対応 OS
- チャンネルを作成
- チャネルにメンバーを招待
- すべてのチャンネルをリスト表示
- 個々のチャット メッセージを送信
- チャネル メッセージに返信
- オンライン Teams 会議を作成
- チャネル メッセージを送信
- グループ チャット メッセージを送信
- 名前からチャネルを取得
- 個々のチャットを取得
- 名前からチームを取得
- ユーザーをチームに招待
- すべてのチャネル メッセージのリストを取得
- すべてのメッセージのリストを取得
- すべてのチーム メンバーのリストを取得
- オンライン Teams 会議を取得
- すべての記録のリストを取得
- すべてのトランスクリプトのリストを取得
- 会議のトランスクリプト/記録をダウンロード
- すべてのレコードのリストを取得
- レコードを挿入
- レコードを更新
- レコードを取得
- レコードを削除
- テクニカル リファレンス
- Microsoft Translator
- Microsoft Vision
- Miro
- Okta
- OpenAI
- Oracle Eloqua
- Oracle NetSuite
- PagerDuty
- Paypal
- PDFMonkey
- Pinecone
- Pipedrive
- QuickBooks Online
- Quip
- Salesforce
- Salesforce Marketing Cloud
- SAP BAPI - Preview
- SAP Build Process Automation - プレビュー
- SAP Cloud for Customer
- SAP Concur
- SendGrid
- ServiceNow
- Shopify
- Slack
- SmartRecruiters
- Smartsheet
- Snowflake
- Stripe
- Sugar Enterprise
- Sugar Professional
- Sugar Sell
- Sugar Serve
- TangoCard
- Todoist
- Trello
- Twilio
- UiPath GenAI アクティビティ
- リリース ノート
- UiPath GenAI アクティビティ パッケージについて
- ベスト プラクティス
- Common Context grounding patterns
- よくある質問
- プロジェクトの対応 OS
- UiPath GenAI アクティビティを使用する
- 対応機種
- IBM WatsonX
- WhatsApp Business
- WooCommerce
- Workable
- Workday
- Workday REST - プレビュー
- X(旧ツイッター)
- Xero
- Youtube
- Zendesk
- Zoho Campaigns
- Zoho Desk
- Zoho Mail
- Zoom
- ZoomInfo
Common Context grounding patterns
The core components of Context grounding are designed to provide a mechanism to support finding pertinent information within and across documents, and surfacing only the most relevant pieces needed to support a high-quality, low-latency generation from an LLM.
ドキュメント内の検索
The Context grounding service helps you find specific information within a single document more effectively. Instead of just matching keywords, it understands the meaning and context of your search query. For example, if you're looking for information about "apple pie recipes" in a cookbook, it would understand that you're interested in desserts and baking, not technology or fruit farming.
ドキュメント全体の検索
Context grounding also helps when you need to find information spread across multiple documents. It can understand the relationships between different pieces of information and provide more relevant results. For example, if you're researching "climate change effects on agriculture" across various scientific papers, it would pull together relevant information from multiple sources, understanding that topics like rainfall patterns, crop yields, and temperature changes are all related to your query.
This means you can use Context grounding for:
-
Data extraction and comparison: Context grounding can automatically identify and pull out specific types of information from documents, then compare them in meaningful ways. Imagine you have a stack of resumes and want to compare candidates' work experiences. The service could extract job titles, durations, and responsibilities, then present them in a way that makes comparison easy, even if the information is formatted differently in each resume.
-
Summarization: Context grounding can create summaries of long documents or multiple related documents. It doesn't just pick out random sentences but understands the key points and overall message. For example, if you have a long report on market trends, the service can provide a summary highlighting the main findings, key statistics, and overall conclusions.