Ontologists and knowledge engineers
Building a domain-specific ontology for a knowledge graph project
The SIMPLE ENTITY mind map template provides a comprehensive ontology of 133 nodes organized into 6 top-level branches: Concrete_Entity, Property, Abstract_Entity, Representation, and Event. This template is used by linguists, ontologists, and knowledge engineers to model entity types and their relationships, covering concrete objects like Artifact (Furniture, Clothing, Vehicle) and Living_Entity (Animal, Human, Vegetal_entity), as well as abstract concepts such as Cognitive_fact and Institution. The Event branch includes detailed subcategories like Speech_act (Directives, Expressives) and Change (Change_of_location, Creation). This SIMPLE ENTITY cheat sheet serves as a structured reference for semantic annotation and ontology development.
Terms and ConditionsBuilding a domain-specific ontology for a knowledge graph project
Annotating semantic roles in a corpus for linguistic research
Teaching foundational concepts in ontology design and entity classification
Open the template in Xmind to browse the six top-level branches and understand the foundational ontology structure.
Navigate through the 133 nodes to examine specific subclasses and qualifiers like Agentive or Telic for precise semantic modeling.
Tailor the entities to your specific domain and export the final map as a PDF or image for your technical documentation.
The template includes 133 nodes across 6 top-level branches: Concrete_Entity, Property, Abstract_Entity, Representation, and Event. It covers entities like Artifact, Human, Animal, and events like Speech_act and Change.
It is organized hierarchically with qualifiers like [Agentive] and [Telic] indicating roles. For example, Artifact has subclasses Furniture, Clothing, and Vehicle, each tagged with [Artifact_ag|Telic].
Yes, you can add, remove, or rename nodes. The template is fully editable in Xmind desktop or web, allowing you to adapt the ontology to your specific domain.
Representation covers symbolic entities like Language, Sign, Information, Number, and Unit_of_measurement, used for modeling how entities are represented.
Yes, the ontology provides fine-grained semantic categories (e.g., Speech_act subclasses) that can be used for semantic role labeling and knowledge graph construction.
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