Semantic Change Ontology
Formally validated ontology for semantic change event types
Ontology Metadata
- Ontology File:
ontologies/semantic-change-ontology-v2.ttl- Event Type Classes:
- 17 classes
- Validation Status:
- PASSED Pellet reasoner consistency check
- Upper Ontology:
- BFO (Basic Formal Ontology) aligned
- Academic Citations:
- 33 citations from 12 papers
- Literature Review:
- 200+ pages of semantic change research
Event Type Classes (17)
| Label | Definition | Citation |
|---|---|---|
| Amelioration | A semantic change event wherein a term acquires increasingly positive connotations, attitudes, or evaluative associations over time. | Jatowt & Duh (2014). Framework for analyzing semantic change. JCDL. Bloomfield (1933) nine classes. |
| Conceptual Bridge | A scholarly contribution that explicitly connects or transfers meaning between different disciplinary contexts, enabling cross-domain semantic evolution. | - |
| Cultural Shift | Semantic change driven by external cultural, societal, or technological factors affecting a term's associations rather than its core denotation. | Kutuzov et al. (2018). Distinguishes cultural shifts from linguistic drifts. |
| Decline | The process by which a particular sense or meaning of a term becomes progressively less common, eventually reaching obsolescence. | Tahmasebi et al. (2021): 'obsolete words slide into obscurity'. |
| Domain Network | The emergence of a domain-specific constellation of meanings and related terms forming a coherent semantic network within a particular field. | - |
| Emergence | The introduction of a previously non-existent meaning or sense for a term within a discourse community. | Tahmasebi et al. (2021): 'new words are coined or borrowed from other languages'. |
| Extensional Drift | Semantic change affecting the extensional definition of a concept via modifications to its instances, measured via Jaccard similarity of instance sets. | Wang et al. (2010, 2011); Stavropoulos et al. (2019). SemaDrift. |
| Inflection Point | A semantic change event characterized by an abrupt, concentrated shift in meaning occurring within a relatively short temporal window. | - |
| Intensional Drift | Semantic change affecting the intensional definition of a concept via modifications to its properties, measured via Jaccard similarity of property sets. | Wang et al. (2010, 2011); Stavropoulos et al. (2019). SemaDrift. |
| Label Drift | Semantic change affecting the rdfs:label or naming of a concept, measured via string similarity (Monge-Elkan). | Wang et al. (2010, 2011); Stavropoulos et al. (2019). SemaDrift. |
| Lexical Replacement | A semantic change process wherein one lexical item supplants another in expressing a particular meaning or concept. | Tahmasebi et al. (2021). Lexical replacement patterns. |
| Pejoration | A semantic change event wherein a term acquires increasingly negative connotations, attitudes, or evaluative associations over time. | Jatowt & Duh (2014). Framework for analyzing semantic change. JCDL. Bloomfield (1933) nine classes. |
| Semantic Drift | A semantic change process characterized by slow, continuous modification of meaning over an extended temporal interval. | Hamilton et al. (2016); Gulla et al. (2010); Stavropoulos et al. (2019). |
| Sense-Level Change | Semantic change measured at the sense level, tracking evolution of specific word meanings or usages identified through clustering. | Montariol et al. (2021). Cluster-based sense-level analysis. |
| Stable Polysemy | A semantic state wherein a term maintains multiple distinct, stable meanings across different discourse communities without one meaning dominating or replacing others. | Hamilton et al. (2016) discuss polysemy as driver of change; this represents stable state without active change. |
| Structural Drift | Semantic change affecting the structural aspects of an ontology including URIs, class hierarchies, and equivalence relationships. | Capobianco et al. (2020). OntoDrift. MEPDaW@ISWC. |
| Word-Level Change | Semantic change measured at the word level, aggregating changes across all senses and usages. | Montariol et al. (2021). Scalable and Interpretable Semantic Change Detection. NAACL. |
Key Features
- Formally validated with Pellet reasoner
- BFO upper ontology alignment
- Academic citations embedded
- Comprehensive literature review
- SKOS definitions and examples
Research Foundation
Event types derived from:
- Hamilton et al. (2016) - Diachronic embeddings
- Kutuzov et al. (2018) - Linguistic drift
- Jatowt & Duh (2014) - Sentiment change
- Tahmasebi et al. (2021) - Comprehensive survey
- Stavropoulos et al. (2019) - Ontology drift
- Capobianco et al. (2020) - Semantic evolution
- And 6 additional sources...