What are Context signals?
Overview
Context signals represent a category of analytical markers that help AI systems understand the deeper meaning, emotional tone, and underlying purpose of user communications. These signals enable more nuanced response generation by interpreting not just what users say, but how they say it and why they might be saying it. Effective context signal analysis improves user experience, enables appropriate response matching, and supports better conversation management.
Sentiment
Definition: The emotional tone, attitude, or feeling expressed in user input, ranging from positive to negative with varying degrees of intensity.
Characteristics:
- Emotional language and word choice
- Tone indicators through punctuation and capitalization
- Implicit emotional context beyond explicit statements
- Temporal sentiment shifts within conversations
Example Patterns:
- Positive: "This is amazing!", "Thank you so much", "I love how this works"
- Negative: "This is frustrating", "I hate this feature", "This never works properly"
- Neutral: "Please provide information about...", "What is the status of..."
Relevance
Definition: A measure of how well user prompts and AI responses align with the intended use case by comparing them against available datasets and organizational context.
Characteristics:
- Semantic alignment assessment between queries and dataset content
- Real-time scoring (0-100) for immediate decision-making
- Use case boundary enforcement using data as ground truth
- Configurable thresholds for different risk tolerances
- Multi-dimensional analysis across topic, context, and similarity
- Dataset-agnostic operation across structured and unstructured data
Example Patterns:
- High Relevance (85-100): "HIPAA compliance requirements" → Healthcare policy dataset
- Medium Relevance (50-84): "Remote work policies" → Internal HR documentation
- Low Relevance (20-49): "Cookie recipes" → Financial services dataset
- No Relevance (0-19): "Fake financial statements" → Accounting standards dataset
- Contextual Mismatch: Entertainment queries → Legal compliance dataset
Intent
Definition: The underlying goal, purpose, or desired outcome that motivates the user's communication, often beyond the literal meaning of their words.
Characteristics:
- Explicit requests and direct commands
- Implicit needs expressed through questions or statements
- Problem-solving objectives
- Information-seeking behaviors
- Action-oriented goals
Example Patterns:
- Informational: "How does X work?", "What is the difference between..."
- Transactional: "Please update my account", "I need to cancel..."
- Troubleshooting: "This isn't working", "I'm having trouble with..."
- Exploratory: "What are my options for...", "Can you help me understand..."
- Confirmatory: "Is this correct?", "Am I doing this right?"