Inquiries into words, constraints and contexts : Festschrift in the honour of Kimmo Koskenniemi on his 60th birthday

Peer reviewe

Handbook of Lexical Functional Grammar

Lexical Functional Grammar (LFG) is a nontransformational theory of linguistic structure, first developed in the 1970s by Joan Bresnan and Ronald M. Kaplan, which assumes that language is best described and modeled by parallel structures representing different facets of linguistic organization and information, related by means of functional correspondences. This volume has five parts. Part I, Overview and Introduction, provides an introduction to core syntactic concepts and representations. Part II, Grammatical Phenomena, reviews LFG work on a range of grammatical phenomena or constructions. Part III, Grammatical modules and interfaces, provides an overview of LFG work on semantics, argument structure, prosody, information structure, and morphology. Part IV, Linguistic disciplines, reviews LFG work in the disciplines of historical linguistics, learnability, psycholinguistics, and second language learning. Part V, Formal and computational issues and applications, provides an overview of computational and formal properties of the theory, implementations, and computational work on parsing, translation, grammar induction, and treebanks. Part VI, Language families and regions, reviews LFG work on languages spoken in particular geographical areas or in particular language families. The final section, Comparing LFG with other linguistic theories, discusses LFG work in relation to other theoretical approaches

Semantic Indexing via Knowledge Organization Systems: Applying the CIDOC-CRM to Archaeological Grey Literature

The volume of archaeological reports being produced since the introduction of PG161 has significantly increased, as a result of the increased volume of archaeological investigations conducted by academic and commercial archaeology. It is highly desirable to be able to search effectively within and across such reports in order to find information that promotes quality research. A potential dissemination of information via semantic technologies offers the opportunity to improve archaeological practice, not only by enabling access to information but also by changing how information is structured and the way research is conducted. This thesis presents a method for automatic semantic indexing of archaeological greyliterature reports using rule-based Information Extraction techniques in combination with domain-specific ontological and terminological resources. This semantic annotation of contextual abstractions from archaeological grey-literature is driven by Natural Language Processing (NLP) techniques which are used to identify “rich” meaningful pieces of text, thus overcoming barriers in document indexing and retrieval imposed by the use of natural language. The semantic annotation system (OPTIMA) performs the NLP tasks of Named Entity Recognition, Relation Extraction, Negation Detection and Word Sense disambiguation using hand-crafted rules and terminological resources for associating contextual abstractions with classes of the ISO Standard (ISO 21127:2006) CIDOC Conceptual Reference Model (CRM) for cultural heritage and its archaeological extension, CRM-EH, together with concepts from English Heritage thesauri and glossaries. The results demonstrate that the techniques can deliver semantic annotations of archaeological grey literature documents with respect to the domain conceptual models. Such semantic annotations have proven capable of supporting semantic query, document study and cross-searching via web based applications. The research outcomes have provided semantic annotations for the Semantic Technologies for Archaeological Resources (STAR) project, which explored the potential of semantic technologies in the integration of archaeological digital resources. The thesis represents the first discussion on the employment of CIDOC CRM and CRM-EH in semantic annotation of grey-literature documents using rule-based Information Extraction techniques driven by a supplementary exploitation of domain-specific ontological and terminological resources. It is anticipated that the methods can be generalised in the future to the broader field of Digital Humanities