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\title{Creating Tools for Morphological Analysis of Sumerian}

\author{Valentin Tablan, Wim Peters, Diana Maynard} 

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\section{Introduction}

Sumerian is a long-extinct language documented throughout the ancient Middle
East, in particular in the south of modern Iraq. It is arguably the first
language for which we have written evidence, the rival candidate being ancient
Egyptian. Sumerian is a language isolate, i.e. no languages related to it
have so far been convincingly identified, although many of its grammatical
features are attested in other living languages outside of the Indo-European
family to which English belongs.

The Electronic Text Corpus of Sumerian Literature (ETCSL), based at the
University of Oxford, aims to make accessible on the web over 350 literary works
composed during the late third and early second millennia BCE. The corpus
comprises Sumerian texts in transliteration, English prose translations and
bibliographical information for each composition. The transliterations and the
translations can be searched, browsed and read online using the tools of the
website.

In this paper we describe the creation of linguistic analysis and corpus search
tools for Sumerian, as part of the development of the ETCSL. This is designed to
enable Sumerian specialists to analyse the texts online and electronically and
to further knowledge about the language.

\section{Creation of Linguistic Analysis Tools for Sumerian}

The main aim of our work is to create a set of tools for performing automatic
morphological analysis of Sumerian. This essentially entails identifying the
part of speech for each word in the corpus (technically, this only involves
nouns and verbs which are the complex cases), separating the lemma part
from the clitics and assigning a morphological function to each of the clitics.
In order to do this, we used the model of Sumerian morphology defined by a
team of Sumerologists, which we then represented in a way that can be
used for automated language processing.

An application has been developed in GATE (General Architecture for Language
Engineering) \cite{Cun02b} for performing morphological analysis on Sumerian. The application
performs the following high-level tasks:

a. Tokenisation: splits the input text into syllables while identifying special
text components such as determiners and markers for damaged regions in the
original clay tablet.

b. Input normalisation: makes explicit the ambiguity caused by some phenomena in
written Sumerian by generating all possible normalised interpretations for each
particular text fragment.

c. Slot fillers look-up: identifies syllables in the input that might denote
morphological inflection.

d. Uninflected words lookup: identifies words that are not inflected by looking
them up in a predefined list.

e. Slot identification: finds sets of candidate morphological slots by grouping
syllables identified at step c) and assigns labels to such slots.

f. Part-of-speech analysis: identifies nouns and verbs.

g. Morphological analysis: generates structure information for the nouns and
verbs by labelling the lemma and all the other constituents.

Although the application was designed to address both nouns and verbs at the
same time, we have concentrated our efforts first on the noun morphology, which
is the simpler case, aiming to direct our attention to the more complex case of
verbs after we get a good understanding of the phenomena we need to address and
we are confident that the architecture of our application is well suited for
Sumerian morphology. Work is currently in progress on improving the analysis of
the verbs.

\section{Evaluation of Results}

To evaluate the results, we obtained a copy of the corpus automatically
annotated with morphological information using a tool developed at the
University of Pennsylvania. Although that annotation is not perfect (the tool
does make some mistakes and also the model of Sumerian morphology used differs
slightly from the one defined by the Oxford group) it does give us a good
indication of where problems might occur. In the current development state of
the application, the results as evaluated over a document containing some 2300
nouns and 1400 verbs are as follows: 
\begin{itemize}
\item recognition of nouns: Precision 59\%, Recall 84\%, F- Measure 69\%
\item recognition of verbs: Precision 65\%, Recall 67\%,  F-Measure 66\%
\item morphological analysis of nouns: Precision 52\%, Recall 73\%, F-Measure 61\%.
\end{itemize}

The only other system for analysing Sumerian automatically that we know of is
the work at Pennsylvania which we are using as the gold standard. So we can only
compare our work with this. However, onsidering the difficulty of the task and
the stage of the work, these results are very promising. We have not yet
measured the morphological analysis of verbs but this is forthcoming. Note also
that since there is much ambiguity between nouns and verbs, errors in the
identification of nouns will generally also have an impact on identification of
verbs, and vice versa, because missing nouns will often be falsely identified as
verbs and so on.
 
 \section{Corpus Search Tools}
 
 The linguistic analysis tools described above are complemented by the
 development of a tool for advanced search and visualisation of linguistic
 information, ANNIC (ANNotations In Context). This provides an alternative
 method of searching the textual data in the corpus, by identifying patterns in
 the corpus that are defined both in terms of the textual information (i.e. the
 actual content) and of metadata (i.e. linguistic annotation and XML/TEI
 markup). The functionality is provided as a plugin in GATE. 

ANNIC consists of two processing resources (index and search) and a visual
resource (viewer). The index processing resource creates an index that is
required for the search process. A corpus can be indexed on words, morphs or
other annotations as appropriate -- these are the segments that will be searched
on in the second stage. The search processing resource takes as input a pattern
on which to search, which can consist of annoations and regular expressions: for
example, one can search on specific combinations of morphs or whole words. A
context size parameter is also set, determining how large a context window
should be used. The viewer is the interface which displays the results. Given a
query to the ANNIC Search engine, it returns the list of documents that contain the
specific pattern, and for each document it returns the patterns and contexts.
Users have the option of viewing the results in different ways according to
their needs.

\section{Conclusions}

In this paper we have described the development of tools for the linguistic
analysis of Sumerian, including a facility to search a corpus of annotated text
for morphological patterns. Work is still ongoing but current results are very
promising. Sumerian is a very difficult language to analyse because there is
much ambiguity, because so little work has been previously done on it and there
are few resources available, and because the rules are extremely complicated. In
the full paper we shall give more details of the components and some further
results.


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