Towards Building a Lexical Ontology Resource Based on Intrinsic Senses of Words

Singh, Navjyoti; Jha, Jyoti

doi:10.5771/9783956503269-198

Cited by 4 publications

(10 citation statements)

References 5 publications

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“…In a single verb many verbal sense-types can be present and different verbs may share same verbal sense-types. There are seven sense-types of verbs have been derived by collecting the fundamental verbs used to define other verbs [13]. These sense-types are inspired from different schools of Indian philosophies.…”

Section: Verbmentioning

confidence: 99%

“…Like verbs, adjectives are also collocative in nature. [13] identifies 12 sense-types. However these can be reduced to 6 pairs.…”

Section: Adjectivesmentioning

confidence: 99%

“…The meaning of a word, from ontological viewpoint, can be understood based on its participation in classes, events and relations. We use a formal ontology that is developed to computationally manipulate language at the level of meanings which have an intrinsic form [13].…”

Section: Introductionmentioning

confidence: 99%

“…Section 2 discusses available lexical resources for Telugu and several types of WSD tasks that were previously developed. Section 3 describes our dataset and shows the statistics of available lexical resources.Section 4 talks about the ontological classification that was formalized for the annotation purpose by [13]. Section 5 describes annotation guidelines and explains the procedure of manual annotation by expert native speakers.…”

Section: Introductionmentioning

confidence: 99%

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Enrichment of OntoSenseNet : Adding a sense-annotated Telugu lexicon

Parupalli¹,

Singh²

2018

EasyChair Preprints

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The paper describes the enrichment of OntoSenseNet-a verbcentric lexical resource for Indian Languages. This resource contains a newly developed Telugu-Telugu dictionary. It is important because native speakers can better annotate the senses when both the word and its meaning are in Telugu. Hence efforts are made to develop a soft copy of Telugu dictionary. It is manually annotated gold standard corpus consisting 8483 verbs, 253 adverbs and 1673 adjectives. Annotations are done by native speakers according to defined annotation guidelines. In this paper, we provide an overview of the annotation procedure and present the validation of our resource through inter-annotator agreement. Concepts of sense-class and sense-type are discussed. Additionally, we discuss the potential of lexical sense-annotated corpora in improving word sense disambiguation (WSD) tasks. Telugu WordNet is crowd-sourced for annotation of individual words in synsets and is compared with the developed sense-annotated lexicon (OntoSenseNet) to examine the improvement. Also, we present a special categorization (spatio-temporal classification) of adjectives.

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Section: Verbmentioning

confidence: 99%

“…Like verbs, adjectives are also collocative in nature. [13] identifies 12 sense-types. However these can be reduced to 6 pairs.…”

Section: Adjectivesmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Enrichment of OntoSenseNet : Adding a sense-annotated Telugu lexicon

Parupalli¹,

Singh²

2018

EasyChair Preprints

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“…OntoSenseNet is a lexical resource developed on the basis of Formal Ontology proposed by (Otra, 2015). The formal ontology follows approaches developed by Yaska, Patanjali and Bhartrihari from Indian linguistic traditions for understanding lexical meaning and by extending approaches developed by Leibniz and Brentano in the modern times.…”

Section: Introductionmentioning

confidence: 99%

Towards Automation of Sense-type Identification of Verbs in OntoSenseNet

Parupalli¹,

Rao

Mamidi

2018

Proceedings of the Sixth International Workshop on Natural Language Processing for Social Media

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In this paper, we discuss the enrichment of a manually developed resource of Telugu lexicon, OntoSenseNet. OntoSenseNet is a ontological sense annotated lexicon that marks each verb of Telugu with a primary and a secondary sense. The area of research is relatively recent but has a large scope of development. We provide an introductory work to enrich the On-toSenseNet to promote further research in Telugu. Classifiers are adopted to learn the sense relevant features of the words in the resource and also to automate the tagging of sense-types for verbs. We perform a comparative analysis of different classifiers applied on OntoSenseNet. The results of the experiment prove that automated enrichment of the resource is effective using SVM classifiers and Adaboost ensemble.

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Proceedings of the Sixth International Workshop on Natural Language Processing for Social Media

2018

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It is our great pleasure to welcome you to the Sixth Workshop on Natural Language Processing for Social Media-SocialNLP 2018, associated with ACL 2018. SocialNLP is an inter-disciplinary area of natural language processing (NLP) and social computing. We hold SocialNLP twice a year: one in the NLP venue, the other in the associated venue such as those for web technology or artificial intelligence. There are three plausible directions of SocialNLP: (1) addressing issues in social computing using NLP techniques; (2) solving NLP problems using information from social media; and (3) handling new problems related to both social computing and natural language processing. Through this workshop, we anticipate to provide a platform for research outcome presentation and head-to-head discussion in the area of SocialNLP, with the hope to combine the insight and experience of prominent researchers from both NLP and social computing domains to contribute to the area of SocialNLP jointly. The submissions to this year's workshop were again of high quality and we had a competitive selection process. We received submissions from Asia, Europe, and the United States, and due to a rigorous review process, we only accepted 7 long oral papers among 19. Thus the acceptance rate was 37 percent. In addition, we are having our first research challenge: EmotionX in the SocialNLP workshop. A total of 18 groups registered for the dataset and at last 5 groups submitted their results successfully. Therefore these year we have 7 research papers, 1 challenge overview paper as well as 5 challenge papers, that is, a total of 13 papers published in the proceedings of the ACL chapter for the SocialNLP 2018 workshop. This year, we are excited to have Dr. Saif Mohammad from National Research Council Canada, and Dr. Yi-Chia Wang from Uber as our keynote speakers. We also encourage attendees to attend the keynote talk presentations to have more discussions with outstanding researchers. Their valuable and insightful talk can and will guide us to a better understanding of the future. Putting together SocialNLP 2018 was a team effort. We first thank the authors for providing the quality content of the program. We are grateful to the program committee members, who worked very hard in reviewing papers and providing feedback for authors. Finally, we especially thank the Workshop Committee Chairs Prof.

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Towards Building a Lexical Ontology Resource Based on Intrinsic Senses of Words

Cited by 4 publications

References 5 publications

Enrichment of OntoSenseNet : Adding a sense-annotated Telugu lexicon

Enrichment of OntoSenseNet : Adding a sense-annotated Telugu lexicon

Towards Automation of Sense-type Identification of Verbs in OntoSenseNet

Proceedings of the Sixth International Workshop on Natural Language Processing for Social Media

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