Morphological analysis for the Maltese language : the challenges of a hybrid system

Maltese is a morphologically rich language with a hybrid morphological system which features both concatenative and non-concatenative processes. This paper analyses the impact of this hybridity on the performance of machine learning techniques for morphological labelling and clustering. In particular, we analyse a dataset of morphologically related word clusters to evaluate the difference in results for concatenative and non-concatenative clusters. We also describe research carried out in morphological labelling, with a particular focus on the verb category. Two evaluations were carried out, one using an unseen dataset, and another one using a gold standard dataset which was manually labelled. The gold standard dataset was split into concatenative and non-concatenative to analyse the difference in results between the two morphological systems.non peer-reviewe

Report on the excavation of a Punic tomb

On 19th November 2001, while two of us (DB, NJC) were preparing a drawn record of the Punic tomb that is situated on Bajda Ridge, Xemxija, a small ceramic bowl (100211) was uncovered from below a few centimetres of soil that covered the inner part of the threshold to the rock-cut chamber (Fig. 1). An official from the Museums Department was informed of the discovery on the same day and a site inspection was carried out. It was realised that more artefacts could lie undisturbed within the chamber and a decision was taken to excavate the deposit. Authorisation for the Department of Classics and Archaeology, University of Malta, to undertake the excavation was received from the Director, Museums Department, and the excavation was completed on the 22nd November. The tomb is located on the ridge, near a path that diverges eastwards from the track that links Pwales valley to the Mistra valley. It is cut in the Upper Coralline limestone that outcrops in the area on a North-South axis and consists of a sub-rectangular chamber that is reached through a low entrance at the bottom of a rectangular shaft (Fig. 1). The tomb appears in an inventory for the first time in 1996 when it was listed in the survey of archaeological sites prepared by Malta University Services for the Planning Authority by Anthony Bonanno in connection with the preparation of the North-West local plan for Malta. The tomb had been examined and photographed by one of us (NCV) in 1992. At the time, it was littered with debris and it was only with difficulty that a view of the chamber could be achieved through the entrance that was partly concealed by an irregular blocking stone. Late in 2000, members of the St Paul's Bay Heritage Group lifted the debris from the trench and cleared the area around the site.peer-reviewe

Automatic grammar rule extraction and ranking for definitions

Learning texts contain much implicit knowledge which is ideally presented to the learner in a structured manner - a typical example being definitions of terms in the text, which would ideally be presented separately as a glossary for easy access. The problem is that manual extraction of such information can be tedious and time consuming. In this paper we describe two experiments carried out to enable the automated extraction of definitions from non-technical learning texts using evolutionary algorithms. A genetic programming approach is used to learn grammatical rules helpful in discriminating between definitions and non-definitions, after which, a genetic algorithm is used to learn the relative importance of these features, thus enabling the ranking of candidate sentences in order of confidence. The results achieved are promising, and we show that it is possible for a Genetic Program to automatically learn similar rules derived by a human linguistic expert and for a Genetic Algorithm to then give a weighted score to those rules so as to rank extracted definitions in order of confidence in an effective manner.peer-reviewe

European language equality

This chapter is a highly abbreviated version of an update (Rosner and C. Borg 2022) to the META-NET White Paper on Maltese (Rosner and Joachimsen 2012). Like its predecessor, the update forms part of a series for all European Languages. Section 1 provides a brief description of the language, its national status, its general typology as a language, and its current usage in the digital sphere. Section 2 gives an overview of technologies and resources that are currently available. Finally, Section 3 frames the main shortcomings of Maltese language technology in terms of fragmentation, and offers some recommendations on how that might be reduced.peer-reviewe

Language technologies for an eLearning scenario

One of the problems with eLearning platforms when collating together documents from different resources is the retrieval of documents and their accessibility. By providing documents with additional metadata using Language Technologies one enables users to access information more effectively. In this paper we present an overview of the objectives and results achieved for the LT4eL Project, which aims at providing Language Technologies to eLearning platforms and to integrate semantic knowledge to facilitate the management, distribution and retrieval of the learning material.peer-reviewe

Definition characterisation through genetic algorithms

The identification of definitions from natural language texts is useful in learning environments, for glossary creation and question answering systems. It is a tedious task to extract such definitions manually, and several techniques have been proposed for automatic definition identification in these domains, including rule-based and statistical methods. These techniques usually rely on linguistic expertise to identify grammatical and word patterns which characterize definitions. In this paper, we look at the use of machine learning techniques, in particular genetic algorithms, to enable the automatic extraction of definitions. Genetic algorithms are used to determine the relative importance of a set of linguistic features which can be present or absent in definitional sentences as a set of numerical weights. These weights provide an importance measure to the set of features. In this work we report on the results of various experiments carried out and evaluate them on an eLearning corpus. We also propose a way forward for discovering such features automatically through genetic programming and suggest how these two techniques can be used together for definition extraction.peer-reviewe

Evolutionary algorithms for definition extraction

Books and other text-based learning material contain implicit information which can aid the learner but which usually can only be accessed through a semantic analysis of the text. Definitions of new concepts appearing in the text are one such instance. If extracted and presented to the learner in form of a glossary, they can provide an excellent reference for the study of the main text. One way of extracting definitions is by reading through the text and annotating definitions manually — a tedious and boring job. In this paper, we explore the use of machine learning to extract definitions from non-technical texts, reducing human expert input to a minimum. We report on experiments we have conducted on the use of genetic programming to learn the typical linguistic forms of definitions and a genetic algorithm to learn the relative importance of these forms. Results are very positive, showing the feasibility of exploring further the use of these techniques in definition extraction. The genetic program is able to learn similar rules derived by a human linguistic expert, and the genetic algorithm is able to rank candidate definitions in an order of confidence.peer-reviewe

Crowd-sourcing evaluation of automatically acquired, morphologically related word groupings

The automatic discovery and clustering of morphologically related words is an important problem with several practical applications. This paper describes the evaluation of word clusters carried out through crowd-sourcing techniques for the Maltese language. The hybrid (Semitic-Romance) nature of Maltese morphology, together with the fact that no large-scale lexical resources are available for Maltese, make this an interesting and challenging problem.peer-reviewe

Automatic definition extraction using parser combinators

The automatic extraction of definitions from natural language texts has various applications such as the creation of glossaries and question-answering systems. In this paper we look at the extraction of definitions from non-technical texts using parser combinators in Haskell. We argue that this approach gives a general and compositional way of characterising natural language definitions. The parsers we develop are shown to be highly effective in the identification of definitions. Furthermore, we show how we can also automatically transform these parsers into other formats to be readily available for use within an eLearning system.peer-reviewe