237:. Another main difference is that UBY models other resources completely and independently from each other, so that UBY can be used as wholesale replacement of each of the contained resources. A collective access to multiple resources is provided through the available resource alignments. Moreover, the LMF model in UBY allows unified way of access for all as well as individual resources. Meanwhile, BabelNet follow an approach similar to WordNet and bakes selected information types into so called Babel Synsets. This makes access and processing of the knowledge more convenient, however, it blurs the lines between the linked knowledge bases. Additionally, BabelNet enriches the original resources, e.g., by providing automatically created translations for concepts which are not lexicalized in a particular language. Although this provides a great boost of coverage for multilingual applications, the automatic inference of information is always prone to a certain degree of error.
229:. At first glance, UBY and BabelNet seem to be identical and competitive projects; however, the two resources follow different philosophies. In its early stage, BabelNet was primarily based on the alignment of WordNet and Knowledge (XXG), which by the very nature of Knowledge (XXG) implied a strong focus on nouns, and especially named entities. Later on, the focus of BabelNet was shifted more towards other parts of speech. UBY, however, was focused from the very beginning on verb information, especially, syntactic information, which is contained in resources, such as
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Kostadin
Cholakov and Judith Eckle-Kohler and Iryna Gurevych : Automated Verb Sense Labelling Based on Linked Lexical Resources. In: Proceedings of the 14th Conference of the European Chapter of the Association for Computational Linguistics (EACL 2014), p. 68-77, Association for Computational
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Judith Eckle-Kohler, Iryna
Gurevych, Silvana Hartmann, Michael Matuschek and Christian M. Meyer. UBY-LMF – A Uniform Model for Standardizing Heterogeneous Lexical-Semantic Resources in ISO-LMF. In: Nicoletta Calzolari and Khalid Choukri and Thierry Declerck and Mehmet Uğur Doğan and Bente Maegaard
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In summary, due to the listed differences between the two resources, the usage of one or the other might be preferred depending on the particular application scenario. In fact, the two resources can be used to provide extensive lexicographic knowledge, especially, if they are linked together. The
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Michael
Matuschek, Tristan Miller and Iryna Gurevych: A Language-independent Sense Clustering Approach for Enhanced WSD. In: Josef Ruppert and Gertrud Faaß: Proceedings of the 12th Konferenz zur Verarbeitung natürlicher Sprache (KONVENS 2014), p. 11-21, Universitätsverlag Hildesheim, October
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Christian M. Meyer and Iryna
Gurevych: To Exhibit is not to Loiter: A Multilingual, Sense-Disambiguated Wiktionary for Measuring Verb Similarity, in: Proceedings of the 24th International Conference on Computational Linguistics (COLING), Vol. 4, p. 1763–1780, December 2012. Mumbai,
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José Gildo de A. Júnior, Ulrich Schiel, and
Leandro Balby Marinho. 2015. An approach for building lexical-semantic resources based on heterogeneous information sources. In Proceedings of the 30th Annual ACM Symposium on Applied Computing (SAC '15). ACM, New York, USA, 402-408.
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Lucie
Flekova and Iryna Gurevych: Personality Profiling of Fictional Characters using Sense-Level Links between Lexical Resources, in: Proceedings of the 2015 Conference on Empirical Methods in Natural Language Processing (EMNLP), September
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version of UBY called lemonUby. lemonUby is based on the lemon model as proposed in the Monnet project. lemon is a model for modeling lexicon and machine-readable dictionaries and linked to the
Semantic Web and the Linked Data cloud.
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J. P. McCrae, P. Cimiano: Mining translations from the web of open linked data, in: Proceedings of the Joint
Workshop on NLP&LOD and SWAIE: Semantic Web, Linked Open Data and Information Extraction, pp 9-13
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Judith Eckle-Kohler, John Philip McCrae and
Christian Chiarcos: lemonUby – a large, interlinked, syntactically-rich lexical resource for ontologies. In: Semantic Web Journal, vol. 6, no. 4, p. 371-378,
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Judith Eckle-Kohler, Iryna
Gurevych, Silvana Hartmann, Michael Matuschek, Christian M Meyer: UBY-LMF – exploring the boundaries of language-independent lexicon models, in Gil Francopoulo,
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Gottfried Herzog, Laurent Romary, Andreas Witt: Standards for Language Resources. Poster Presentation at the META-FORUM 2013 – META Exhibition, September 2013, Berlin, Germany.
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UBY is available as part of the open resource repository DKPro. DKPro UBY is a Java framework for creating and accessing sense-linked lexical resources in accordance with the
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and Joseph Mariani and Jan Odijk and Stelios Piperidis: Proceedings of the 8th International Conference on Language Resources and Evaluation (LREC), p. 275--282, May 2012.
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is a format for standardizing lexical resources for Natural Language Processing (NLP). UBY-LMF conforms to the ISO standard for lexicons:
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and combines information from several expert-constructed and collaboratively constructed resources for English and German.
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Matuschek, Michael: Word Sense Alignment of Lexical Resources. Technische Universität, Darmstadt , (2015)
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open and well-documented structure of the two resource provide a crucial milestone to achieve this goal.
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UBY - A Large-Scale Unified Lexical-Semantic Resource Based on LMF
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Laurent Romary: TEI and LMF crosswalks. CoRR abs/1301.2444 (2013)
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UBY has been successfully used in different NLP tasks such as
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Text is available under the Creative Commons Attribution-ShareAlike License. Additional terms may apply.