KaifAhmad1andClaude Sonnet 4.6
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title, description, icon
| title | description | icon |
|---|---|---|
| Glossary | Reference of terms and concepts used throughout Semantica. | book |
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. Semantica's temporal model uses valid_from/valid_until on nodes and edges.
BiTemporalFact — A fact with both a valid time (when it was true in the world) and a transaction time (when it was recorded in the system).
Allen Interval Algebra — A system of 13 relations for temporal ordering of intervals (before, after, meets, overlaps, during, starts, finishes, equals, and their inverses). Supported since v0.4.0.
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).
Ontology Hub — Semantica's v0.5.0 visual browser UI for the full ontology lifecycle: visual editor, SHACL Studio, alignment authoring, health dashboard, and version control.
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.
SHACL (Shapes Constraint Language) — A W3C standard for validating RDF graphs against a set of shapes (constraints). Semantica can auto-generate and validate SHACL shapes.
SKOS (Simple Knowledge Organization System) — A W3C standard for representing controlled vocabularies, taxonomies, and thesauri.
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 metrics include PageRank, betweenness, 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.
Distance Intelligence — Semantica's v0.5.0 feature for semantic neighborhood exploration: N×N distance matrices, ego-mode visualization, and distance band classification.
Distance Band — A classification of a node's proximity to a target: near, mid, or far, based on semantic embedding distance thresholds.
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.
Datalog — A declarative logic programming language used for knowledge base queries. Semantica's DatalogEngine supports recursive Horn clause rules with bottom-up semi-naive fixpoint semantics (v0.4.0).
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.
W3C PROV-O — The W3C standard ontology for provenance. Semantica tracks lineage across all 17 modules in a PROV-O compliant format.
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.
XXE (XML External Entity) — A security vulnerability in XML parsers. Semantica's XMLIngestor (v0.5.0) uses an XXE-safe lxml backend.
SSRF (Server-Side Request Forgery) — A security vulnerability where a server can be induced to make requests to unintended destinations. Semantica validates base_url at construction time to prevent SSRF.
See Also
- Core Concepts — deeper explanation of key ideas
- Getting Started — first steps
- Modules Guide — every module explained
- API Reference — technical reference