Ilya Khait

This paper describes work on the morphological and syntactic annotation of Sumerian cuneiform as a model for low resource languages in general. Cuneiform texts are invaluable sources for the study of history, languages, economy, and cultures of Ancient Mesopotamia and its surrounding regions. Assyriology, the discipline dedicated to their study, has vast research potential, but lacks the modern means for computational processing and analysis. Our project, Machine Translation and Automated Analysis of Cuneiform Languages, aims to fill this gap by bringing together corpus data, lexical data, linguistic annotations and object metadata. The project's main goal is to build a pipeline for machine translation and annotation of Sumerian Ur III administrative texts. The rich and structured data is then to be made accessible in the form of (Linguistic) Linked Open Data (LLOD), which should open them to a larger research community. Our contribution is twofold: in terms of language technology, our work represents the first attempt to develop an integrative infrastructure for the annotation of morphology and syntax on the basis of RDF technologies and LLOD resources. With respect to Assyriology, we work towards producing the first syntactically annotated corpus of Sumerian.

Linguistic Linked Open Data (LLOD) is a flourishing line of research in the language resource community, so far mostly adopted for selected aspects of linguistics, natural language processing and the semantic web, as well as for practical applications in localization and lexicography. Yet, computational philology seems to be somewhat decoupled from the recent progress in this area: even though LOD as a concept is gaining significant popularity in Digital Humanities, existing LLOD standards and vocabularies are not widely used in this community, and philological resources are underrepresented in the LLOD cloud diagram (http://linguistic-lod.org/llod-cloud). In this paper, we present an application of Linguistic Linked Open Data in Assyriology. We describe the LLOD edition of a linguistically annotated corpus of Sumerian, as well as its linking with lexical resources, repositories of annotation terminology, and the museum collections in which the artifacts bearing these texts are kept. The chosen corpus is the Electronic Text Corpus of Sumerian Royal Inscriptions, a well curated and linguistically annotated archive of Sumerian text, in preparation for the creating and linking of other corpora of cuneiform texts, such as the corpus of Ur III administrative and legal Sumerian texts, as part of the Machine Translation and Automated Analysis of Cuneiform Languages project (https://cdli-gh.github.io/mtaac/).

Assyriology, the discipline that studies cuneiform sources and their context, has enormous potential for the application of computational linguistics theory and method on account of the significant quantity of transcribed texts that are available in digital form but that remain as yet largely unexploited. As part of the Machine Translation and Automated Analysis of Cuneiform Languages project (https://cdli-gh.github.io/mtaac/), we aim to bring together corpus data, lexical data, linguistic annotations and object metadata in order to contribute to resolving data processing and integration challenges in the field of Assyriology as a whole, as well as for related fields of research such as linguistics and history. Data sparsity presents a challenge to our goal of the automated transliteration of the administrative texts of the Ur III period. To mitigate this situation we have undertaken to annotate the whole corpus. To this end we have developed an annotation pipeline to facilitate the annotation of our gold corpus. This toolset can be re-employed to annotate any Sumerian text and will be integrated into the Cuneiform Digital Library Initiative (https://cdli.ucla.edu) infrastructure. To share these new data, we have also mapped our data to existing LOD and LLOD ontologies and vocabularies. This article provides details on the processing of Sumerian linguistic data using our pipeline, from raw transliterations to rich and structured data in the form of (L)LOD. We describe the morphological and syntactic annotation, with a particular focus on the publication of our datasets as LOD. This application of LLOD in Assyriology is unique and involves the concept of a LLOD edition of a linguistically annotated corpus of Sumerian, as well as linking with lexical resources, repositories of annotation terminology, and finally the museum collections in which the artifacts bearing these inscribed texts are kept.