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This paper deals with the semantics of the Old English verb. It contributes to an area of
the linguistics of Old English to which less attention has been paid than to other aspects
of this language, such as phonology, morphology and syntax. The works engaging in Old
English semantics are limited, being the studies concerning the category of the verb as
such as well as the organization of the verbal category even scarcer. This research points
at the border between morphology and semantics so as to design and define a semantic
map of the verbal derivatives of Old English strong verb primes that incorporates graph
theory by means of a system of visual representation. The aim of this study is, firstly, to
analyse the semantic relations holding between primitive and derived verbs in terms of
two inherent features of verbs, particulary troponymy and Aktionart. Then, to design a
semantic map of the Old English lexical paradigms to visually represent the results of this
analysis. While troponymy is analysed in the wider context of FrameNet, the Aktionsart
of verbs is studied within the framework of Role and Reference Grammar (Van Valin and
LaPolla 1997; Van Valin 2005, 2014). The concept of lexical paradigm is based on Martín
Arista (2012, 2013). In order to carry out this investigation, 328 lexical paradigms based
on strong verbs derived from verbs are analysed. The data of analysis have been drawn
from the lexical database of Old English Nerthus. The results of the analysis are depicted
by means of the semantic map of the Old English verb BELGAN ‘to make angry, anger,
offend, irritate, provoke; to incense; to become angry; to be angry’. In the semantic map,
meanings are organised as synsets (sets of cognitive synonyms). The semantic map
methodology allows to exhaustively combine the analysis of troponymy and Aktionsart
into a single network from the core to the periphery of each derivational paradigm based
on a strong verb. The main conclusion is that the adoption of the semantic map
methodology, in this investigation, has allowed to exhaustively combine both analyses
showing that semantic maps are more applicable and flexible than earlier studies suggest.