pwc-archive/papers-with-abstracts huggingface dataset:
WME 3.0: An Enhanced and Validated Lexicon of Medical Concepts
Authors: Anupam Mondal, Dipankar Das, Erik Cambria, Sivaji Bandyopadhyay
Date: 2018-01-01 00:00:00
Proceeding: GWC 2018 1
Tasks: Descriptive

Information extraction in the medical domain is laborious and time-consuming due to the insufficient number of domain-specific lexicons and lack of involvement of domain experts such as doctors and medical practitioners. Thus, in the present work, we are motivated to design a new lexicon, WME 3.0 (WordNet of Medical Events), which contains over 10,000 medical concepts along with their part of speech, gloss (descriptive explanations), polarity score, sentiment, similar sentiment words, category, affinity score and gravity score features. In addition, the manual annotators help to validate the overall as well as individual category level of medical concepts of WME 3.0 using Cohen’s Kappa agreement metric. The agreement score indicates almost correct identification of medical concepts and their assigned features in WME 3.0.
Using Context to Improve the Spanish WordNet Translation
Authors: Alfonso Methol, Guillermo López, Juan Álvarez, Luis Chiruzzo, Dina Wonsever
Date: 2018-01-01 00:00:00
Proceeding: GWC 2018 1
Tasks: Translation

We present some strategies for improving the Spanish version of WordNet, part of the MCR, selecting new lemmas for the Spanish synsets by translating the lemmas of the corresponding English synsets. We used four simple selectors that resulted in a considerable improvement of the Spanish WordNet coverage, but with relatively lower precision, then we defined two context based selectors that improved the precision of the translations.
Towards Cross-checking WordNet and SUMO Using Meronymy
Authors: Javier Álvez, German Rigau
Date: 2018-01-01 00:00:00
Proceeding: GWC 2018 1

We describe the practical application of a black-box testing methodology for the validation of the knowledge encoded in WordNet, SUMO and their mapping by using automated theorem provers. In this paper,weconcentrateonthepart-whole information provided by WordNet and create a large set of tests on the basis of few question patterns. From our preliminary evaluation results, we report on some of the detected inconsistencies.
Comparing Two Thesaurus Representations for Russian
Authors: Natalia Loukachevitch, German Lashevich, Boris Dobrov
Date: 2018-01-01 00:00:00
Proceeding: GWC 2018 1
Tasks: Vocal Bursts Valence Prediction

In the paper we presented a new Russian wordnet, RuWordNet, which was semi-automatically obtained by transformation of the existing Russian thesaurus RuThes. At the first step, the basic structure of wordnets was reproduced: synsets’ hierarchy for each part of speech and the basic set of relations between synsets (hyponym-hypernym, part-whole, antonyms). At the second stage, we added causation, entailment and domain relations between synsets. Also derivation relations were established for single words and the component structure for phrases included in RuWordNet. The described procedure of transformation highlights the specific features of each type of thesaurus representations.
Towards Mapping Thesauri onto plWordNet
Authors: Marek Maziarz, Maciej Piasecki
Date: 2018-01-01 00:00:00
Proceeding: GWC 2018 1
Tasks: Keyword Extraction

plWordNet, the wordnet of Polish, has become a very comprehensive description of the Polish lexical system. This paper presents a plan of its semi-automated integration with thesauri, terminological databases and ontologies, as a further necessary step in its development. This will improve linking of plWordNet into Linked Open Data, and facilitate applications in, e.g., WSD, keyword extraction or automated metadata generation. We present an overview of resources relevant to Polish and a plan for their linking to plWordNet.
Investigating English Affixes and their Productivity with Princeton WordNet
Authors: Verginica Mititelu
Date: 2018-01-01 00:00:00
Proceeding: GWC 2018 1

Such a rich language resource like Princeton WordNet, containing linguistic information of different types (semantic, lexical, syntactic, derivational, dialectal, etc.), is a thesaurus which is worth both being used in various language-enabled applications and being explored in order to study a language. In this paper we show how we used Princeton WordNet version 3.0 to study the English affixes. We extracted pairs of base-derived words and identified the affixes by means of which the derived words were created from their bases. We distinguished among four types of derivation depending on the type of overlapping between the senses of the base word and those of the derived word that are linked by derivational relations in Princeton WordNet. We studied the behaviour of affixes with respect to these derivation types. Drawing on these data, we inferred about their productivity.
Mapping WordNet Instances to Wikipedia
Authors: John P. McCrae
Date: 2018-01-01 00:00:00
Proceeding: GWC 2018 1
Tasks: Articles

Lexical resource differ from encyclopaedic resources and represent two distinct types of resource covering general language and named entities respectively. However, many lexical resources, including Princeton WordNet, contain many proper nouns, referring to named entities in the world yet it is not possible or desirable for a lexical resource to cover all named entities that may reasonably occur in a text. In this paper, we propose that instead of including synsets for instance concepts PWN should instead provide links to Wikipedia articles describing the concept. In order to enable this we have created a gold-quality mapping between all of the 7,742 instances in PWN and Wikipedia (where such a mapping is possible). As such, this resource aims to provide a gold standard for link discovery, while also allowing PWN to distinguish itself from other resources such as DBpedia or BabelNet. Moreover, this linking connects PWN to the Linguistic Linked Open Data cloud, thus creating a richer, more usable resource for natural language processing.
Mapping WordNet Concepts with CPA Ontology
Authors: Svetla Koeva, Cvetana Dimitrova, Valentina Stefanova, Dimitar Hristov
Date: 2018-01-01 00:00:00
Proceeding: GWC 2018 1
Tasks: Vocal Bursts Type Prediction

The paper discusses the enrichment of WordNet data through merging of WordNet concepts and Corpus Pattern Analysis (CPA) semantic types. The 253 CPA semantic types are mapped to the respective WordNet concepts. As a result of mapping, the hyponyms of a synset to which a CPA semantic type is mapped inherit not only the respective WordNet semantic primitive but also the CPA semantic type.
Improving Wordnets for Under-Resourced Languages Using Machine Translation
Authors: Bharathi Raja Chakravarthi, Mihael Arcan, John P. McCrae
Date: 2018-01-01 00:00:00
Proceeding: GWC 2018 1
Tasks: Machine Translation, Translation

Wordnets are extensively used in natural language processing, but the current approaches for manually building a wordnet from scratch involves large research groups for a long period of time, which are typically not available for under-resourced languages. Even if wordnet-like resources are available for under-resourced languages, they are often not easily accessible, which can alter the results of applications using these resources. Our proposed method presents an expand approach for improving and generating wordnets with the help of machine translation. We apply our methods to improve and extend wordnets for the Dravidian languages, i.e., Tamil, Telugu, Kannada, which are severly under-resourced languages. We report evaluation results of the generated wordnet senses in term of precision for these languages. In addition to that, we carried out a manual evaluation of the translations for the Tamil language, where we demonstrate that our approach can aid in improving wordnet resources for under-resourced Dravidian languages.
Semantic Feature Structure Extraction From Documents Based on Extended Lexical Chains
Authors: Terry Ruas, William Grosky
Date: 2018-01-01 00:00:00
Proceeding: GWC 2018 1
Tasks: Retrieval, Sentence

The meaning of a sentence in a document is more easily determined if its constituent words exhibit cohesion with respect to their individual semantics. This paper explores the degree of cohesion among a document’s words using lexical chains as a semantic representation of its meaning. Using a combination of diverse types of lexical chains, we develop a text document representation that can be used for semantic document retrieval. For our approach, we develop two kinds of lexical chains: (i) a multilevel flexible chain representation of the extracted semantic values, which is used to construct a fixed segmentation of these chains and constituent words in the text; and (ii) a fixed lexical chain obtained directly from the initial semantic representation from a document. The extraction and processing of concepts is performed using WordNet as a lexical database. The segmentation then uses these lexical chains to model the dispersion of concepts in the document. Representing each document as a high-dimensional vector, we use spherical k-means clustering to demonstrate that our approach performs better than previous techniques.
Toward a Semantic Concordancer
Authors: Adam Pease, Andrew Cheung
Date: 2018-01-01 00:00:00
Proceeding: GWC 2018 1
Tasks: Dependency Parsing

Concordancers are an accepted and valuable part of the tool set of linguists and lexicographers. They allow the user to see the context of use of a word or phrase in a corpus. A large enough corpus, such as the Corpus Of Contemporary American English, provides the data needed to enumerate all common uses or meanings. One challenge is that there may be too many results for short search phrases or common words when only a specific context is desired. However, finding meaningful groupings of usage may be impractical if it entails enumerating long lists of possible values, such as city names. If a tool existed that could create some semantic abstractions, it would free the lexicographer from the need to resort to customized development of analysis software. To address this need, we have developed a Semantic Concordancer that uses dependency parsing and the Suggested Upper Merged Ontology (SUMO) to support linguistic analysis at a level of semantic abstraction above the original textual elements. We show how this facility can be employed to analyze the use of English prepositions by non-native speakers. We briefly introduce condordancers and then describe the corpora on which we applied this work. Next we provide a detailed description of the NLP pipeline followed by how this captures detailed semantics. We show how the semantics can be used to analyze errors in the use of English prepositions by non-native speakers of English. Then we provide a description of a tool that allows users to build semantic search specifications from a set of English examples and how those results can be employed to build rules that translate sentences into logical forms. Finally, we summarize our conclusions and mention future work.
Using OpenWordnet-PT for Question Answering on Legal Domain
Authors: Pedro Delfino, Bruno Cuconato, Guilherme Paulino-Passos, Gerson Zaverucha, Alexandre Rademaker
Date: 2018-01-01 00:00:00
Proceeding: GWC 2018 1
Tasks: Question Answering, Topic coverage

In order to practice a legal profession in Brazil, law graduates must be approved in the OAB national unified bar exam. For their topic coverage and national reach, the OAB exams provide an excellent benchmark for the performance of legal information systems, as it provides objective metrics and are challenging even for humans, as only 20% of its candidates are approved. After constructing a new data set on the exams and doing shallow experiments on it, we now employ the OpenWordnet-PT to verify whether using word senses and relations we can improve previous results. We discuss the results, possible future ideas and the additions to the OpenWordnet-PT that we made.
Implementation of the Verb Model in plWordNet 4.0
Authors: Agnieszka Dziob, Maciej Piasecki
Date: 2018-01-01 00:00:00
Proceeding: GWC 2018 1

The paper presents an expansion of the verb model for plWordNet – the wordnet of Polish. A modified system of constitutive features (register, aspect and verb classes), synset and lexical relations is presented. A special attention is given to the proposed new relations and changes in the verb classification. We discuss also the results of its verification by application to the description of a relatively large sample of Polish verbs. The model introduces a new class of relations, namely non-constitutive synset relations that are shared among lexical units, but describe, not define synsets. The proposed model is compared to the entailment relations in other wordnets, and the description of verbs based on valency frames.
Public Apologies in India - Semantics, Sentiment and Emotion
Authors: Sangeeta Shukla, Rajita Shukla
Date: 2018-01-01 00:00:00
Proceeding: GWC 2018 1
Tasks: Document Classification, Opinion Mining, Sentiment Analysis

This paper reports a pilot study related to public apologies in India, with reference to certain keywords found in them. The study is of importance as the choice of lexical items holds importance which goes beyond the surface meaning of the words. The analysis of the lexical items has been done using interlinked digital lexical resources which, in future, can lend this study to computational tasks related to opinion mining, sentiment analysis and document classification. The study attempts an in-depth psycholinguistic analysis of whether the apology conveys a sincerity of intent or is it a mere ritualistic exercise to control and repair damage.
Derivational Relations in Arabic WordNet
Authors: Mohamed Ali Batita, Mounir Zrigui
Date: 2018-01-01 00:00:00
Proceeding: GWC 2018 1

When derivational relations deficiency exists in a wordnet, such as the Arabic WordNet, it makes it very difficult to exploit in the natural language processing community. Such deficiency is raised when many wordnets follow the same development path of Princeton WordNet. A rule-based approach for Arabic derivational relations is proposed in this paper to deal with this deficiency. The proposed approach is explained step by step. It involves the gathering of lexical entries that share the same root, into a bag of words. Rules are then used to affect the appropriate derivational relations, i.e. to relate existing words in the AWN, involving part-of-speech switch. The method is implemented using Java. Manual verification by a lexicographer takes place to ensure good results. The described approach gave good results. It could be useful for other morphologically complex languages as well.
Extending Wordnet to Geological Times
Authors: Henrique Muniz, Fabricio Chalub, Alexandre Rademaker, Valeria de Paiva
Date: 2018-01-01 00:00:00
Proceeding: GWC 2018 1

This paper describes work extending Princeton WordNet to the domain of geological texts, associated with the time periods of the geological eras of the Earth History. We intend this extension to be considered as an example for any other domain extension that we might want to pursue. To provide this extension, we first produce a textual version of Princeton WordNet. Then we map a fragment of the International Commission on Stratigraphy (ICS) ontologies to WordNet and create the appropriate new synsets. We check the extended ontology on a small corpus of sentences from Gas and Oil technical reports and realize that more work needs to be done, as we need new words, new senses and new compounds in our extended WordNet.
Towards Emotive Annotation in plWordNet 4.0
Authors: Monika Zaśko-Zielińska, Maciej Piasecki
Date: 2018-01-01 00:00:00
Proceeding: GWC 2018 1

The paper presents an approach to building a very large emotive lexicon for Polish based on plWordNet. An expanded annotation model is discussed, in which lexical units (word senses) are annotated with basic emotions, fundamental human values and sentiment polarisation. The annotation process is performed manually in the 2+1 scheme by pairs of linguists and psychologies. Guidelines referring to the usage in corpora, substitution tests as well linguistic properties of lexical units (e.g. derivational associations) are discussed. Application of the model in a substantial extension of the emotive annotation of plWordNet is presented. The achieved high inter-annotator agreement shows that with relatively small workload a promising emotive resource can be created.
The Company They Keep: Extracting Japanese Neologisms Using Language Patterns
Authors: James Breen, Timothy Baldwin, Francis Bond
Date: 2018-01-01 00:00:00
Proceeding: GWC 2018 1

We describe an investigation into the identification and extraction of unrecorded potential lexical items in Japanese text by detecting text passages containing selected language patterns typically associated with such items. We identified a set of suitable patterns, then tested them with two large collections of text drawn from the WWW and Twitter. Samples of the extracted items were evaluated, and it was demonstrated that the approach has considerable potential for identifying terms for later lexicographic analysis.
Towards a principled approach to sense clustering – a case study of wordnet and dictionary senses in Danish
Authors: Bolette Pedersen, Manex Agirrezabal, Sanni Nimb, Ida Olsen, Sussi Olsen
Date: 2018-01-01 00:00:00
Proceeding: GWC 2018 1
Tasks: Clustering

Our aim is to develop principled methods for sense clustering which can make existing lexical resources practically useful in NLP – not too fine-grained to be operational and yet finegrained enough to be worth the trouble. Where traditional dictionaries have a highly structured sense inventory typically describing the vocabulary by means of mainand subsenses, wordnets are generally fine-grained and unstructured. We present a series of clustering and annotation experiments with 10 of the most polysemous nouns in Danish. We combine the structured information of a traditional Danish dictionary with the ontological types found in the Danish wordnet, DanNet. This constellation enables us to automatically cluster senses in a principled way and improve inter-annotator agreement and wsd performance.
WordnetLoom – a Multilingual Wordnet Editing System Focused on Graph-based Presentation
Authors: Tomasz Naskręt, Agnieszka Dziob, Maciej Piasecki, Chakaveh Saedi, António Branco
Date: 2018-01-01 00:00:00
Proceeding: GWC 2018 1

The paper presents a new re-built and expanded, version 2.0 of WordnetLoom – an open wordnet editor. It facilitates work on a multilingual system of wordnets, is based on efficient software architecture of thin client, and offers more flexibility in enriching wordnet representation. This new version is built on the experience collected during the use of the previous one for more than 10 years of plWordNet development. We discuss its extensions motivated by the collected experience. A special focus is given to the development of a variant for the needs of MultiWordnet of Portuguese, which is based on a very different wordnet development model.
Translation Equivalence and Synonymy: Preserving the Synsets in Cross-lingual Wordnets
Authors: Oi Yee Kwong
Date: 2018-01-01 00:00:00
Proceeding: GWC 2018 1
Tasks: Translation

The Princeton WordNet for English was founded on the synonymy relation, and multilingual wordnets are primarily developed by creating equivalent synsets in the respective languages. The process would often rely on translation equivalents obtained from existing bilingual dictionaries. This paper discusses some observations from the Chinese Open Wordnet, especially from the adjective subnet, to illuminate potential blind spots of the approach which may lead to the formation of non-synsets in the new wordnet. With cross-linguistic differences duly taken into account, alternative representations of cross-lingual lexical relations are proposed to better capture the language-specific properties. It is also suggested that such cross-lingual representation encompassing the cognitive as well as linguistic aspects of meaning is beneficial for a lexical resource to be used by both humans and computers.
Lexical Perspective on Wordnet to Wordnet Mapping
Authors: Ewa Rudnicka, Francis Bond, Łukasz Grabowski, Maciej Piasecki, Tadeusz Piotrowski
Date: 2018-01-01 00:00:00
Proceeding: GWC 2018 1
Tasks: Machine Translation, Translation

The paper presents a feature-based model of equivalence targeted at (manual) sense linking between Princeton WordNet and plWordNet. The model incorporates insights from lexicographic and translation theories on bilingual equivalence and draws on the results of earlier synset-level mapping of nouns between Princeton WordNet and plWordNet. It takes into account all basic aspects of language such as form, meaning and function and supplements them with (parallel) corpus frequency and translatability. Three types of equivalence are distinguished, namely strong, regular and weak depending on the conformity with the proposed features. The presented solutions are language-neutral and they can be easily applied to language pairs other than Polish and English. Sense-level mapping is a more fine-grained mapping than the existing synset mappings and is thus of great potential to human and machine translation.
ReferenceNet: a semantic-pragmatic network for capturing reference relations.
Authors: Piek Vossen, Filip Ilievski, Marten Postrma
Date: 2018-01-01 00:00:00
Proceeding: GWC 2018 1
Tasks: Word Embeddings

In this paper, we present ReferenceNet: a semantic-pragmatic network of reference relations between synsets. Synonyms are assumed to be exchangeable in similar contexts and also word embeddings are based on sharing of local contexts represented as vectors. Co-referring words, however, tend to occur in the same topical context but in different local contexts. In addition, they may express different concepts related through topical coherence, and through author framing and perspective. In this paper, we describe how reference relations can be added to WordNet and how they can be acquired. We evaluate two methods of extracting event coreference relations using WordNet relations against a manual annotation of 38 documents within the same topical domain of gun violence. We conclude that precision is reasonable but recall is lower because the WordNet hierarchy does not sufficiently capture the required coherence and perspective relations.
Wordnet-based Evaluation of Large Distributional Models for Polish
Authors: Maciej Piasecki, Gabriela Czachor, Arkadiusz Janz, Dominik Kaszewski, Paweł Kędzia
Date: 2018-01-01 00:00:00
Proceeding: GWC 2018 1
Tasks: Word Embeddings

The paper presents construction of large scale test datasets for word embeddings on the basis of a very large wordnet. They were next applied for evaluation of word embedding models and used to assess and compare the usefulness of different word embeddings extracted from a very large corpus of Polish. We analysed also and compared several publicly available models described in literature. In addition, several large word embeddings models built on the basis of a very large Polish corpus are presented.