Sample ontologies for Knowledge Graph entity extraction

This topic provides sample ontologies that can be used to configure the Knowledge Graph Entity Extractor for common use cases. Each example illustrates how entities, attributes, and relationships can be modeled to support accurate extraction, normalization, and downstream reasoning within the knowledge graph. The samples are intended as reference starting points, not prescriptive models. You can adapt them to match your domain vocabulary, data sources, and agent or workflow requirements.

For each use case, the ontology demonstrates:

  • The types of entities to extract.

  • Key properties associated with each entity.

  • Relationships that enable meaningful connections and queries.

Use these examples to accelerate initial setup, validate your configuration approach, or inform custom ontology design for more advanced scenarios.

Pharmaceutical research and drug development ontology

This ontology models entities and relationships commonly found in pharmaceutical research, drug development, and regulatory workflows. It is useful for extracting structured knowledge from clinical, regulatory, and scientific content to support discovery, compliance tracking, and analytics.

ENTITIES
 
PHARMACEUTICAL_COMPANY (e.g., Pfizer)
DRUG (e.g., Keytruda)
DRUG_CLASS (e.g., Antibiotic)
ACTIVE_INGREDIENT (e.g., Paracetamol)
DISEASE (e.g., Lung Cancer)
THERAPEUTIC_AREA (e.g., Oncology)
CLINICAL_TRIAL (e.g., KEYNOTE-024)
TRIAL_PHASE (e.g., Phase III)
REGULATORY_AUTHORITY (e.g., FDA)
APPROVAL (e.g., FDA Approval 2020)
PATIENT_POPULATION (e.g., Adults)
SIDE_EFFECT (e.g., Nausea)
DOSAGE_FORM (e.g., Tablet)
MANUFACTURING_FACILITY (e.g., Pfizer Hyderabad Plant)

RELATIONSHIPS

DEVELOPS (PHARMACEUTICAL_COMPANY → DRUG)
MANUFACTURES (PHARMACEUTICAL_COMPANY → DRUG)
PRODUCED_AT (DRUG → MANUFACTURING_FACILITY)
CONTAINS_ACTIVE_INGREDIENT (DRUG → ACTIVE_INGREDIENT)
BELONGS_TO_CLASS (DRUG → DRUG_CLASS)
INDICATED_FOR (DRUG → DISEASE)
TREATS (DRUG_CLASS → DISEASE)
ASSOCIATED_WITH_AREA (DISEASE → THERAPEUTIC_AREA)
TESTED_IN (DRUG → CLINICAL_TRIAL)
HAS_PHASE (CLINICAL_TRIAL → TRIAL_PHASE)
CONDUCTED_BY (CLINICAL_TRIAL → PHARMACEUTICAL_COMPANY)
APPROVED_BY (APPROVAL → REGULATORY_AUTHORITY)
APPROVES (REGULATORY_AUTHORITY → DRUG)
HAS_APPROVAL (DRUG → APPROVAL)
TARGETS_POPULATION (DRUG → PATIENT_POPULATION) 
HAS_SIDE_EFFECT (DRUG → SIDE_EFFECT) 
AVAILABLE_AS (DRUG → DOSAGE_FORM)

Legal case management ontology

This ontology represents the core entities and interactions involved in legal cases and litigation processes. It enables structured extraction of parties, filings, evidence, courts, and outcomes from legal documents and case records.

ENTITIES
 
LEGAL_ENTITY – Person or organization involved in a case
PERSON – Human participant
ORGANIZATION – Company, agency, institution
ROLE – Plaintiff, Defendant, Witness, Accused
LEGAL_CASE – Case or lawsuit
LEGAL_DOCUMENT – Any legal filing or document
EVIDENCE – Evidence submitted in the case
EVIDENCE_CATEGORY – Type of evidence (digital, documentary, etc.)
JUDGMENT – Court’s final decision
COURT – Judicial authority
LAW – Statutes, acts, sections
DATE – Dates associated with events
LOCATION – Court or event locations

RELATIONSHIPS
 
FILED_BY (LEGAL_CASE → LEGAL_ENTITY) – Case filer
FILED_AGAINST (LEGAL_CASE → LEGAL_ENTITY) – Case target
HEARD_BY (LEGAL_CASE → COURT) – Court handling case
REPRESENTED_BY (LEGAL_ENTITY → PERSON) – Legal representative
HAS_DOCUMENT (LEGAL_CASE → LEGAL_DOCUMENT) – Linked documents
SUBMITTED_BY (LEGAL_DOCUMENT → LEGAL_ENTITY) – Document submitter
REFERS_TO_LAW (LEGAL_CASE/LEGAL_DOCUMENT → LAW) – Law cited
HAS_EVIDENCE (LEGAL_CASE → EVIDENCE) – Evidence included
EVIDENCE_SUBMITTED_BY (EVIDENCE → LEGAL_ENTITY) – Evidence provider
EVIDENCE_TYPE (EVIDENCE → EVIDENCE_CATEGORY) – Category of evidence
RESULTED_IN (LEGAL_CASE → JUDGMENT) – Final outcome
ISSUED_BY (JUDGMENT → COURT) – Court issuing judgment
JUDGMENT_DATE (JUDGMENT → DATE) – Judgment date
PARTY_ROLE (LEGAL_ENTITY → ROLE) – Assigned role
CASE_LOCATION (LEGAL_CASE → LOCATION) – Where case is filed/heard

Contract and Agreement Analysis Ontology

This ontology is designed to capture the structure and obligations within legal agreements and contracts. It supports extracting parties, clauses, rights, obligations, and governing terms to enable contract analysis, compliance checks, and risk assessment.

ENTITIES
 
AGREEMENT – Any legal agreement/contract
PARTY – Person or organization involved
PERSON – Individual party
ORGANIZATION – Corporate/Institutional party
CLAUSE – Specific section of the agreement
OBLIGATION – Duty or responsibility defined in agreement
RIGHT – Right or entitlement defined in agreement
TERM – Duration/time period of the agreement
EFFECTIVE_DATE – Start date
EXPIRY_DATE – End date
SIGNATURE – Signature information
GOVERNING_LAW – Applicable law/section
PAYMENT_TERM – Payment-related clause
CONFIDENTIALITY_TERM – Confidentiality requirements
TERMINATION_CLAUSE – Termination conditions
JURISDICTION – Court/location governing disputes
AMENDMENT – Modification to agreement

RELATIONSHIPS
 
HAS_PARTY (AGREEMENT → PARTY) – Parties involved
PARTY_TYPE (PARTY → PERSON/ORGANIZATION) – Identifies party type
HAS_CLAUSE (AGREEMENT → CLAUSE) – Clauses included
HAS_OBLIGATION (CLAUSE → OBLIGATION) – Obligations defined
HAS_RIGHT (CLAUSE → RIGHT) – Rights defined
HAS_TERM (AGREEMENT → TERM) – Agreement duration
HAS_EFFECTIVE_DATE (AGREEMENT → EFFECTIVE_DATE) – Start date
HAS_EXPIRY_DATE (AGREEMENT → EXPIRY_DATE) – End date
SIGNED_BY (SIGNATURE → PARTY) – Who signed
HAS_SIGNATURE (AGREEMENT → SIGNATURE) – Signature records
GOVERNED_BY (AGREEMENT → GOVERNING_LAW) – Applicable law
HAS_PAYMENT_TERM (AGREEMENT → PAYMENT_TERM) – Payment rules
HAS_CONFIDENTIALITY_TERM (AGREEMENT → CONFIDENTIALITY_TERM) – Confidentiality terms
HAS_TERMINATION_CLAUSE (AGREEMENT → TERMINATION_CLAUSE) – Termination rules
HAS_JURISDICTION (AGREEMENT → JURISDICTION) – Dispute jurisdiction
HAS_AMENDMENT (AGREEMENT → AMENDMENT) – Modifications

Legal Case Brief and Judicial Reasoning Ontology

This ontology models the analytical structure of legal case briefs, including facts, issues, arguments, holdings, and reasoning. It is suited for summarization, precedent analysis, and legal research scenarios.

ENTITIES
 
CASE_BRIEF – Summary of a legal case
CASE_NAME – Official case title
COURT – Court that heard the case
JUDGE – Judge(s) involved
PARTY – Any party in the case
PLAINTIFF – Party filing the case
DEFENDANT – Party the case is against
FACT – Factual background
ISSUE – Legal question(s) presented
ARGUMENT – Arguments by parties
HOLDING – Court’s answer to issues
REASONING – Court’s rationale
JUDGMENT – Final outcome/order
LAW – Statutes/sections cited
PRECEDENT – Prior case referenced
DATE – Relevant dates (hearing, judgment)
EVIDENCE – Key evidence referred in briefing

RELATIONSHIPS

HAS_CASE_NAME (CASE_BRIEF → CASE_NAME) – Title of case
HEARD_BY (CASE_BRIEF → COURT) – Court that heard case
JUDGED_BY (CASE_BRIEF → JUDGE) – Judge(s) involved
HAS_PARTY (CASE_BRIEF → PARTY) – Parties included
HAS_PLAINTIFF (CASE_BRIEF → PLAINTIFF) – Filing party
HAS_DEFENDANT (CASE_BRIEF → DEFENDANT) – Opposing party
HAS_FACT (CASE_BRIEF → FACT) – Key facts
HAS_ISSUE (CASE_BRIEF → ISSUE) – Legal issues
HAS_ARGUMENT (CASE_BRIEF → ARGUMENT) – Party arguments
HAS_HOLDING (CASE_BRIEF → HOLDING) – Court’s answer
HAS_REASONING (CASE_BRIEF → REASONING) – Court’s rationale
HAS_JUDGMENT (CASE_BRIEF → JUDGMENT) – Final result
REFERS_TO_LAW (CASE_BRIEF → LAW) – Cited laws
CITES_PRECEDENT (CASE_BRIEF → PRECEDENT) – Prior cases referenced
MENTIONS_EVIDENCE (CASE_BRIEF → EVIDENCE) – Evidence summarized
HAS_DATE (CASE_BRIEF → DATE) – Important dates