Developing an automated semantic analysis system for Early Modern English

As reported by Wilson and Rayson (1993) and Rayson and Wilson (1996), the UCREL semantic analysis system (USAS) has been designed to undertake the automatic semantic analysis of present-day English (henceforth PresDE) texts. In this paper, we report on the feasibility of (re)training the USAS system to cope with English from earlier periods, specifically the Early Modern English (henceforth EmodE) period. We begin by describing how effectively the existing system tagged a training corpus prior to any modifications. The training corpus consists of newsbooks dating from December 1653 – May 1654, and totals approximately 613,000.words. We then document the various adaptations that we made to the system in an attempt to improve its efficiency, and the results we achieved when we applied the modified system to two newsbook texts, and an additional text from the Lampeter Corpus (i.e. a text that was not part of the original training corpus). To conclude, we propose a design for a modified semantic tagger for EmodE texts, that contains an ‘intelligent’ spelling regulariser, that is, a system that has been designed so as to regularise spellings in their ‘correct’ context.