Abstract syntax as interlingua: Scaling up the grammatical framework from controlled languages to robust pipelines

Syntax is an interlingual representation used in compilers. Grammatical Framework (GF) applies the abstract syntax idea to natural languages. The development of GF started in 1998, first as a tool for controlled language implementations, where it has gained an established position in both academic and commercial projects. GF provides grammar resources for over 40 languages, enabling accurate generation and translation, as well as grammar engineering tools and components for mobile and Web applications. On the research side, the focus in the last ten years has been on scaling up GF to wide-coverage language processing. The concept of abstract syntax offers a unified view on many other approaches: Universal Dependencies, WordNets, FrameNets, Construction Grammars, and Abstract Meaning Representations. This makes it possible for GF to utilize data from the other approaches and to build robust pipelines. In return, GF can contribute to data-driven approaches by methods to transfer resources from one language to others, to augment data by rule-based generation, to check the consistency of hand-annotated corpora, and to pipe analyses into high-precision semantic back ends. This article gives an overview of the use of abstract syntax as interlingua through both established and emerging NLP applications involving GF

Normalizing English for Interlingua : Multi-channel Approach to Global Machine Translation

The paper tries to demonstrate that when English is used as interlingua in translating between two languages it can be normalized for reducing unnecessary ambiguity. Current usage of English often omits such critical features as the relative pronoun and the conjunction for marking the beginning of the subordinate clause. In addition to causing ambiguity, the practice also makes it difficult to produce correct structures in target language. If the source language makes such structures explicit, it is possible to carry this information through the whole translation chain into target language. If we consider English language as an interlingua in a multilingual translation environment, we should make the intermediate stage as little ambiguous as possible. There are also other possibilities for reducing ambiguity, such as selection of less ambiguous translation equivalents. Also, long noun compounds, which are often ambiguous, can be presented in unambiguous form, when the linguistic knowledge of the source language is included.Non peer reviewe

Sharing Semantic Resources

The Semantic Web is an extension of the current Web in which information, so far created for human consumption, becomes machine readable, “enabling computers and people to work in cooperation”. To turn into reality this vision several challenges are still open among which the most important is to share meaning formally represented with ontologies or more generally with semantic resources. This Semantic Web long-term goal has many convergences with the activities in the field of Human Language Technology and in particular in the development of Natural Language Processing applications where there is a great need of multilingual lexical resources. For instance, one of the most important lexical resources, WordNet, is also commonly regarded and used as an ontology. Nowadays, another important phenomenon is represented by the explosion of social collaboration, and Wikipedia, the largest encyclopedia in the world, is object of research as an up to date omni comprehensive semantic resource. The main topic of this thesis is the management and exploitation of semantic resources in a collaborative way, trying to use the already available resources as Wikipedia and Wordnet. This work presents a general environment able to turn into reality the vision of shared and distributed semantic resources and describes a distributed three-layer architecture to enable a rapid prototyping of cooperative applications for developing semantic resources

The Lexical Grid: Lexical Resources in Language Infrastructures

Language Resources are recognized as a central and strategic for the development of any Human Language Technology system and application product. they play a critical role as horizontal technology and have been recognized in many occasions as a priority also by national and spra-national funding a number of initiatives (such as EAGLES, ISLE, ELRA) to establish some sort of coordination of LR activities, and a number of large LR creation projects, both in the written and in the speech areas

Linking Discourse Marker Inventories

The paper describes the first comprehensive edition of machine-readable discourse marker lexicons. Discourse markers such as and, because, but, though or thereafter are essential communicative signals in human conversation, as they indicate how an utterance relates to its communicative context. As much of this information is implicit or expressed differently in different languages, discourse parsing, context-adequate natural language generation and machine translation are considered particularly challenging aspects of Natural Language Processing. Providing this data in machine-readable, standard-compliant form will thus facilitate such technical tasks, and moreover, allow to explore techniques for translation inference to be applied to this particular group of lexical resources that was previously largely neglected in the context of Linguistic Linked (Open) Data

Models to represent linguistic linked data

As the interest of the Semantic Web and computational linguistics communities in linguistic linked data (LLD) keeps increasing and the number of contributions that dwell on LLD rapidly grows, scholars (and linguists in particular) interested in the development of LLD resources sometimes find it difficult to determine which mechanism is suitable for their needs and which challenges have already been addressed. This review seeks to present the state of the art on the models, ontologies and their extensions to represent language resources as LLD by focusing on the nature of the linguistic content they aim to encode. Four basic groups of models are distinguished in this work: models to represent the main elements of lexical resources (group 1), vocabularies developed as extensions to models in group 1 and ontologies that provide more granularity on specific levels of linguistic analysis (group 2), catalogues of linguistic data categories (group 3) and other models such as corpora models or service-oriented ones (group 4). Contributions encompassed in these four groups are described, highlighting their reuse by the community and the modelling challenges that are still to be faced

Linking discourse marker inventories

The paper describes the first comprehensive edition of machine-readable discourse marker lexicons. Discourse markers such as and, because, but, though or thereafter are essential communicative signals in human conversation, as they indicate how an utterance relates to its communicative context. As much of this information is implicit or expressed differently in different languages, discourse parsing, context-adequate natural language generation and machine translation are considered particularly challenging aspects of Natural Language Processing. Providing this data in machine-readable, standard-compliant form will thus facilitate such technical tasks, and moreover, allow to explore techniques for translation inference to be applied to this particular group of lexical resources that was previously largely neglected in the context of Linguistic Linked (Open) Data

Investigating the universality of a semantic web-upper ontology in the context of the African languages

Ontologies are foundational to, and upper ontologies provide semantic integration across, the Semantic Web. Multilingualism has been shown to be a key challenge to the development of the Semantic Web, and is a particular challenge to the universality requirement of upper ontologies. Universality implies a qualitative mapping from lexical ontologies, like WordNet, to an upper ontology, such as SUMO. Are a given natural language family's core concepts currently included in an existing, accepted upper ontology? Does SUMO preserve an ontological non-bias with respect to the multilingual challenge, particularly in the context of the African languages? The approach to developing WordNets mapped to shared core concepts in the non-Indo-European language families has highlighted these challenges and this is examined in a unique new context: the Southern African languages. This is achieved through a new mapping from African language core concepts to SUMO. It is shown that SUMO has no signi ficant natural language ontology bias.ComputingM. Sc. (Computer Science