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Back to NLP Topics A Knowledge Graph (KG) converts static FAQ text into a structured conversational experience. It supports two models: an ontology-based model using hierarchical terms, and an LLM-based Few-Shot model that requires no ontology.

Knowledge Graph Types

Ontology Knowledge Graph

Organizes FAQs using terms, synonyms, traits, and context. When a user asks a question, the engine matches utterance tokens against KG nodes (path qualification), then scores shortlisted questions using cosine similarity. Enable: Go to Automation AI > Natural Language > NLU Config > Engine Tuning > Knowledge Graph and select Ontology Model. How it works:
  1. User utterance and KG nodes are tokenized; n-grams extracted (up to quad-gram).
  2. Tokens are mapped to KG nodes to get indices.
  3. Path qualification: paths are shortlisted based on term coverage and mandatory term presence.
  4. Best match is selected by cosine scoring over shortlisted questions.
Training process:
  1. All terms/nodes and their synonyms are indexed.
  2. A flattened path is established for each KG intent using those indices.

Few-Shot Knowledge Graph

Uses Kore.ai’s LLM to identify FAQs by semantic similarity—no ontology needed. Add all FAQs to the root node. Enable: Go to Automation AI > Natural Language > NLU Config > Engine Tuning > Knowledge Graph and select Few-Shot Model. Prerequisites before enabling:
  • Requires NLP V3 and Ranking & Resolver V2 (auto-updated when enabled).
  • Embedding model options: BGE M3, MPNet, LaBSE.
  • When switching from Ontology KG: Default terms are retained until updated, then become Organizer terms (can be set as Mandatory).
  • Only Mandatory terms support path-level synonyms.
How it works: The LLM computes semantic similarity between the user utterance and FAQs, returning a similarity score. The score determines match type (definite, probable, etc.) based on thresholds. Matched intents are sent to Ranking and Resolver to select the winner.

Selecting Your KG Type

Starting with v10.1, Few-Shot is the default for new KGs under NLP V3 in English. Go to Automation > Knowledge AI > FAQs to switch types.
Before changing KG type, back up your existing graph by creating a new app version or exporting as JSON or CSV. Changes are captured in App Settings > Change Logs.

Feature Comparison

FeatureFew-Shot KGOntology KG
Ontology StructureOptionalMandatory
Default TermsNo (exception: existing terms when switching from Ontology)Yes
Mandatory TermsYesYes
Organizer TermsYesYes
Path QualificationNoYes
TagsYesYes
SynonymsYes (Mandatory Terms and Tags only)Yes
Path-Level SynonymsYes (Mandatory Terms only)Yes
Knowledge Graph SynonymsYes (Mandatory Terms only)Yes
TraitsYesYes
ContextYesYes
Stop WordsYesYes
KG Import/ExportYesYes
Auto-Generate KGYesYes
Bot SynonymsYesYes
Lemmatization using Parts of SpeechNoYes
Path CoverageNoYes
Search in AnswerNoYes
Qualify Contextual PathsNoYes
Auto-CorrectionYesYes
Min/Definitive Level for KG IntentYesYes
KG Suggestions CountYesYes
Proximity of Suggested MatchesYesYes
Manage Long ResponsesYesYes
Intent PreconditionsYesYes
Context OutputYesYes
Supports All Platform LanguagesYesYes