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The focus of this study will be on one of the most fundamental concepts for the knowledge classification: the endurant/perdurant dichotomy for classification of entities.
This fundamental classification of entities roughly corresponds to what is called continuant and occurrent in philosophy (Gangemi et al. 2003, Grenon and Smith 2004).
Another approach within algorithmic cheminformatics that is closely related to the hierarchical classification of entities within the chemical domain is that of computing systematic names for structures and structures from names.
Hence the implication is that it is NOT the shape or other perceivable physical properties, but rather the entity's continuity of existence in time that plays a central role in the classification of entities in our knowledge systems.
Taxonomic and phylogenetic approaches to community analysis impose either a discrete or a hierarchical classification of entities (Mishler & Donoghue, 1982; Cohan & Perry, 2007).
Extended from the idea of semantic networks, the recognition task includes the classification of entities (nodes) and their associated events (edges).
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Classification of candidate entities into categories of interest is carried out by leveraging principles from distributional semantics.
The identification and classification of biological entities is important, since it allows its study, control and exploitation.
For the domain of biologically interesting chemistry, the Chemical Entities of Biological Interest ontology (ChEBI) [6] provides a classification of chemical entities such as atoms, molecules and ions.
Nadeau and Sekine (2007: 8) list punctuation among the "features most often used for the recognition and classification of named entities".
In related work extending the notion of parthood and features for classification of chemical entities, Stevens describes an approach using OWL for the classification of the atoms in the periodic table [49].
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