Modelling Lexical Resources as Linked Data

In the last years a rapid emergence of lexical resources has evolved in the Semantic Web. Whereas most of the linguistic information is already machine-readable, we found that morphological information is mostly absent or only contained in semi-structured strings. An integration of morphemic data has not yet been undertaken due to the lack of existing domain-specific ontologies and explicit morphemic data. In this paper, we present the Multilingual Morpheme Ontology called MMoOn Core which can be regarded as the first comprehensive ontology for the linguistic domain of morphological language data. It will be described how crucial concepts like morphs, morphemes, word forms and meanings are represented and interrelated and how language-specific morpheme inventories can be created as a new possibility of morphological datasets. The aim of the MMoOn Core ontology is to serve as a shared semantic model for linguists and NLP researchers alike to enable the creation, conversion, exchange, reuse and enrichment of morphological language data across different data-dependent language sciences. Therefore, various use cases are illustrated to draw attention to the cross-disciplinary potential which can be realized with the MMoOn Core ontology in the context of the existing Linguistic Linked Data research landscape.

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Using Multilingual Lexical Resources for Extending the Linked Data Cloud

Theorie, Semantik und Organisation von Wissen ◽

10.5771/9783956503269-246 ◽

2017 ◽

pp. 246-250

Author(s):

E. W. De Luca

Keyword(s):

Linked Data ◽

Lexical Resources

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Improving Machine Translation through Linked Data

Prague Bulletin of Mathematical Linguistics ◽

10.1515/pralin-2017-0033 ◽

2017 ◽

Vol 108 (1) ◽

pp. 355-366 ◽

Cited By ~ 2

Author(s):

Ankit Srivastava ◽

Georg Rehm ◽

Felix Sasaki

Keyword(s):

Machine Translation ◽

Language Processing ◽

Linked Data ◽

Statistical Machine Translation ◽

Open Data ◽

Knowledge Bases ◽

Data Sets ◽

Lexical Resources ◽

Unknown Words ◽

Cross Lingual

Abstract With the ever increasing availability of linked multilingual lexical resources, there is a renewed interest in extending Natural Language Processing (NLP) applications so that they can make use of the vast set of lexical knowledge bases available in the Semantic Web. In the case of Machine Translation, MT systems can potentially benefit from such a resource. Unknown words and ambiguous translations are among the most common sources of error. In this paper, we attempt to minimise these types of errors by interfacing Statistical Machine Translation (SMT) models with Linked Open Data (LOD) resources such as DBpedia and BabelNet. We perform several experiments based on the SMT system Moses and evaluate multiple strategies for exploiting knowledge from multilingual linked data in automatically translating named entities. We conclude with an analysis of best practices for multilingual linked data sets in order to optimise their benefit to multilingual and cross-lingual applications.

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Models to represent linguistic linked data

Natural Language Engineering ◽

10.1017/s1351324918000347 ◽

2018 ◽

Vol 24 (6) ◽

pp. 811-859 ◽

Cited By ~ 3

Author(s):

J. BOSQUE-GIL ◽

J. GRACIA ◽

E. MONTIEL-PONSODA ◽

A. GÓMEZ-PÉREZ

Keyword(s):

Computational Linguistics ◽

Linked Data ◽

Language Resources ◽

Lexical Resources ◽

Analysis Group ◽

Group 4 ◽

Service Oriented ◽

Group 3 ◽

Group 2 ◽

Group 1

AbstractAs 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.

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Aggregation and Maintenance of Multilingual Linked Data

Semi-Automatic Ontology Development ◽

10.4018/978-1-4666-0188-8.ch008 ◽

2012 ◽

pp. 201-225

Author(s):

Ernesto William De Luca

Keyword(s):

Linked Data ◽

Open Data ◽

Relevant Information ◽

User Preferences ◽

Linked Open Data ◽

Lexical Resources ◽

Lexical Information ◽

Lexical Resource

In this chapter, the author presents his approach to aggregating and maintaining Multilingual Linked Data. He describes Lexical Resources and Lexical Linked Data, presenting a hybridization that ports the largest lexical resource EuroWordNet to the Linked Open Data cloud, interlinking it with other lexical resources. Furthermore, he shows the LexiRes RDF/OWL tool that gives the possibility to navigate this lexical information, helping authors of already available lexical resources in deleting or restructuring concepts using automatic merging methods. The chapter is concluded by a discussion on personalizing information according to user preferences, filtering relevant information while taking into account the multilingual background of the user.

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Embodied displacements in young German children’s storytelling

Research on Children and Social Interaction ◽

10.1558/rcsi.37311 ◽

2019 ◽

Vol 3 (1-2) ◽

pp. 168-195 ◽

Cited By ~ 3

Author(s):

Vivien Heller

Keyword(s):

Picture Book ◽

Book Reading ◽

Lexical Resources ◽

Narrative Space ◽

Multimodal Analysis ◽

Different Types ◽

German Speaking ◽

Picture Book Reading ◽

The Given

This paper is concerned with embodied processes of joint imagination in young children’s narrative interactions. Based on Karl Bühler’s notion of ‘deixis in the imagination’, it examines in detail how a 19-month-old German-speaking child, engaged in picture book reading with his mother, brings about different subtypes of deixis in the imagination by either ‘displacing’ what is absent into the given order of perception (e.g. by using the hand as a token for an object) or displacing his origo to an imagined space (e.g. by kinaesthetically aligning his body with an imagined body and animating his movements). Drawing on multimodal analysis and the concept of layering in interaction, the study analyses the ways in which the picture book as well as deictic, depictive, vocal and lexical resources are coordinated to evoke a narrative space, co-enact the storybook character’s experiences and produce reciprocal affect displays. Findings demonstrate that different types of displacement are in play quite early in childhood; displacements in the dimension of space and person are produced through layerings of spaces, voices and bodies.

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