KaifAhmad1
d3b579208c
## Documentation Changes ### 📚 Major Improvements - **Cleaned up all documentation files** - Removed redundant content and improved clarity - **Restructured Resources section** - Removed unnecessary files, kept only essential ones - **Added Snowflake integration** - Complete integration guide with examples - **Improved navigation** - Better organization and user experience ### 🗂️ File Changes - **docs/concepts.md** - Rewritten to be clean and user-friendly - **docs/modules.md** - Updated with current modules and removed emojis - **docs/glossary.md** - Reorganized thematically instead of alphabetically - **docs/getting-started.md** - Made more concise and practical - **docs/community.md** - Clean, focused community guide - **docs/contributing.md** - Clear contribution guidelines - **docs/faq.md** - Comprehensive FAQ with practical answers - **docs/license.md** - Clean license explanation - **docs/css/custom.css** - Fixed CSS syntax and organization ### 🔧 Technical Changes - **mkdocs.yml** - Updated navigation, removed redundant files - **docs/integrations/snowflake.md** - New comprehensive Snowflake guide - **docs/reference/ingest.md** - Added Snowflake references - **Removed files**: changelog.md, release-guide.md, change_management_usage.md, community-projects.md, architecture.md, governance.md, citation.md ### 🎯 Benefits - **Better user experience** - Clean, easy to navigate documentation - **Reduced redundancy** - No duplicate or unnecessary content - **Professional quality** - Enterprise-ready documentation - **Consistent style** - Uniform formatting across all files This commit includes all documentation improvements while maintaining the main branch's stability.
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Glossary
Comprehensive reference of terms and concepts used in Semantica and semantic intelligence.
!!! tip "Quick Reference" Looking for a specific term? Use your browser's search function (Ctrl+F) to find terms quickly.
Core Concepts
Agent
An autonomous AI system that can perceive its environment, reason about information, and take actions to achieve specific goals. In Semantica, agents use knowledge graphs for memory and reasoning.
Entity
A distinct object or concept in the real world, such as a person, place, organization, or event. Entities are the fundamental building blocks of knowledge graphs.
Knowledge Graph (KG)
A structured representation of knowledge using entities (nodes) and relationships (edges). KGs enable reasoning, querying, and semantic analysis of data.
Relationship
A connection between two entities that describes how they relate to each other (e.g., "works_for", "located_in", "founded_by").
Semantic
Relating to meaning in language or logic. Semantic understanding goes beyond keywords to comprehend context and intent.
Data Processing
Ingestion
The process of loading data from various sources (files, databases, APIs, streams) into a system for processing.
Normalization
The process of standardizing data into a consistent format (e.g., converting dates to ISO format, standardizing entity names).
Parsing
Extracting structured information from unstructured or semi-structured documents like PDFs, Word documents, or web pages.
Chunking
Breaking down large documents into smaller, manageable pieces while preserving context and meaning.
Artificial Intelligence
LLM (Large Language Model)
A type of artificial intelligence model trained on vast amounts of text data, capable of understanding and generating human-like text.
RAG (Retrieval Augmented Generation)
A technique that enhances LLM responses by retrieving relevant information from a knowledge base before generating an answer.
GraphRAG (Graph-Augmented Retrieval Augmented Generation)
An advanced RAG approach that combines vector search with knowledge graph traversal to provide more accurate and contextually relevant information to LLMs.
Inference
The process of deriving new facts or conclusions from existing knowledge using logical rules.
Knowledge Graph Components
Node
A vertex in a graph representing an entity or concept.
Edge
A connection between two nodes representing a relationship.
Property
An attribute or characteristic of an entity or relationship (e.g., name, date, confidence score).
Triplet
A basic unit of knowledge in RDF, consisting of a subject, predicate, and object (e.g., <Apple_Inc> <founded_by> <Steve_Jobs>).
Temporal Graph
A knowledge graph that tracks changes over time, allowing queries about the state of the graph at specific time points.
Entity Recognition & Extraction
Named Entity Recognition (NER)
The process of identifying and classifying named entities in text into predefined categories such as persons, organizations, locations, dates, and more.
Relationship Extraction
The task of identifying and extracting semantic relationships between entities in text.
Entity Resolution
The process of determining when two entity mentions refer to the same real-world entity, also known as entity linking or deduplication.
Coreference Resolution
The task of determining when two or more expressions in text refer to the same entity (e.g., "Apple" and "the company" referring to Apple Inc.).
Event Detection
The task of identifying and classifying events (e.g., acquisitions, partnerships, announcements) in text.
Ontology & Schema
Ontology
A formal specification of concepts, relationships, and constraints in a domain, typically expressed in OWL (Web Ontology Language).
Class
In ontologies, a category or type of entity (e.g., Person, Organization, Location).
Axiom
A statement or rule that is accepted as true without proof, used in ontologies to define logical constraints and relationships.
OWL (Web Ontology Language)
A W3C standard language for defining and instantiating ontologies on the web.
Property
In ontologies, a relationship or attribute that connects entities or describes their characteristics.
Data Storage & Retrieval
Embedding
A dense vector representation of text, images, or other data that captures semantic meaning in a continuous vector space. Used for similarity search and semantic matching.
Vector Store
A database optimized for storing and searching high-dimensional vectors, used for semantic similarity search.
Triplet Store
A database designed specifically for storing and querying RDF triplets.
Graph Database
A database designed specifically for storing and querying graph-structured data.
Hybrid Search
A search strategy that combines multiple retrieval methods, typically vector search and keyword search, to improve accuracy.
Graph Analytics
Centrality
A measure of the importance or influence of a node in a graph. Common centrality metrics include PageRank, betweenness centrality, and closeness centrality.
PageRank
An algorithm used to measure the importance of nodes in a graph based on the structure of incoming links.
Community Detection
The process of identifying groups or clusters of densely connected nodes in a graph.
Graph Analytics
The application of graph algorithms (e.g., centrality, community detection) to gain insights from the structure of a knowledge graph.
Query Languages
Cypher
A declarative query language for graph databases, particularly Neo4j.
SPARQL
A query language for RDF data, similar to SQL for relational databases.
RDF (Resource Description Framework)
A W3C standard for representing information about resources in the form of subject-predicate-object triplets.
Data Quality
Conflict Resolution
The process of handling contradictory information from multiple sources in a knowledge graph.
Deduplication
The process of identifying and removing duplicate records or entities from a dataset.
Data Provenance
Information about the origin, history, and lineage of data, including sources, timestamps, and transformations.
Technical Terms
API (Application Programming Interface)
A set of functions and protocols that allow different software applications to communicate with each other.
OCR (Optical Character Recognition)
Technology that converts images of text (e.g., scanned documents, photos) into machine-readable text.
Pipeline
A sequence of data processing steps that transform raw data into a desired output format.
Vector
A mathematical representation of data as an array of numbers, used in embeddings to capture semantic meaning.
Visualization
The graphical representation of data, such as knowledge graphs, embeddings, or analytics.
Web Scraping
The automated process of extracting data from websites.
Semantica-Specific Terms
Semantic Layer
An abstraction layer that provides a unified, business-friendly view of data by adding context, relationships, and meaning to raw data.
Semantic Network
A knowledge representation that uses a graph structure to represent concepts and their relationships.
Change Management
The process of tracking and managing changes to knowledge graphs over time, including version control and audit trails.
Provenance Tracking
W3C PROV-O compliant tracking of data lineage and source attribution.
See Also
- Core Concepts - Deep dive into fundamental concepts
- Getting Started - Begin your journey with Semantica
- Modules Guide - Complete module overview
- API Reference - Technical documentation
Need Help?
- Documentation: Getting Started
- Examples: Cookbook
- Community: Discord
- Issues: GitHub Issues
- Support: Contact Us