Natural language processing (NLP) can be extremely useful for transforming conference notes into actionable items by extracting key points, tasks, and deadlines from unstructured material.
- NLP Models for Text Parsing - To evaluate meeting notes, use pre-trained NLP models such as GPT-3 or other specialized tools. These models can detect action items by extracting verbs (e.g., "resolve," "implement") and linking them to specific subjects or responsibilities.
- Set up task extraction algorithms. Create algorithms to search for action keywords like "assigned," "due," "complete," and "follow-up." These keywords identify probable action items in the notes.
- Use Named Entity Recognition (NER) - NLP models can recognize individuals, dates, and locations in meeting notes, allowing you to automatically assign action items to the appropriate person and set deadlines depending on context.
- Integrate with Task Management applications: After extracting action items, send them automatically to project management applications such as Jira, Asana, or ClickUp. This is possible through API connectors or automation solutions such as Zapier.
- Use NLP to categorize meeting notes by topic (e.g., "Operations," "Product Development"), making related action items easier to track and follow up on.
Using NLP, you can streamline the process of translating meeting talks into specific action items, saving time and ensuring that nothing is overlooked.
