PhD thesis - School of Informatics - University of Edinburgh

Chapter 5. Parsing English Inclusions 117
cessing inclusions. Most of the time, they are unknown words and, as they originate
from another language, standard methods for unknown word guessing (suffix strip-
ping, etc.) are unlikely to be successful. Furthermore, the fact that inclusions are often
multi-word expressions (e.g., named entities or code-switches) means that simply part-
of-speech (POS) tagging them accurately is not sufficient: the parser positing a phrase
boundary within an inclusion is likely to severely decrease accuracy.
After a brief summary of related work in Section 5.1, this chapter then describes
an extrinsic evaluation of this classifier for parsing. It is shown that recognising and
dealing with English inclusions via a special annotation label improves the accuracy
of parsing. In particular, this chapter demonstrates that detecting English inclusions
in German text improves the performance of two German parsers, a treebank-induced
parser as well as a parser based on a hand-crafted grammar (Sections 5.3 and 5.4). Cru-
cially, the former parser requires modifications of its underlying grammar to deal with
the inclusions, the latter’s grammar is already designed to deal with multi-word expres-
sions signalled in the input. Both parsers and necessary modifications are described in
detail in Sections 5.3.1 and 5.4.1. The data used for all the parsing experiments is
described in 5.2.
5.1 Related Work
Previous work on inclusion detection exists in the TTS literature (Pfister and Roms-
dorfer, 2003; Farrugia, 2005; Marcadet et al., 2005), which is reviewed in detail in
Sections 2.2.1.1 and 2.2.1.2. Here, the aim is to design a system that recognises for-
eign inclusions on the word and sentence level and functions as the front-end to a
polyglot TTS synthesiser. Similar initial efforts have been undertaken in the field of
lexicography where the importance of recognising anglicisms from the perspective of
lexicographers responsible for updating lexicons and dictionaries has been acknowl-
edged (Andersen, 2005) (see also Section 2.2.1.4). In the context of parsing, however,
there has been little focus on this issue. Although Forst and Kaplan (2006) have stated
the need for dealing with foreign inclusions in parsing as they are detrimental to a
parser’s performance, they do not substantiate this claim using numeric results.
Previous work reported in this thesis have focused on devising a classifier that de-
tects anglicisms and other English inclusions in text written in other languages, namely