ymoslem/acl-abstracts huggingface dataset:
A Two-Phase Approach for Building Vietnamese WordNet (2016)

Wordnets play an important role not only in linguistics but also in natural language processing (NLP). This paper reports major results of a project which aims to construct a wordnet for Vietnamese language. We propose a two-phase approach to the construction of Vietnamese WordNet employing available language resources and ensuring Vietnamese specific linguistic and cultural characteristics. We also give statistical results and analyses to show characteristics of the wordnet.
Extending the WN-Toolkit: dealing with polysemous words in the dictionary-based strategy (2016)

In this paper we present an extension of the dictionary-based strategy for wordnet construction implemented in the WN-Toolkit. This strategy allows the extraction of information for polysemous English words if definitions and/or semantic relations are present in the dictionary. The WN-Toolkit is a freely available set of programs for the creation and expansion of wordnets using dictionary-based and parallel-corpus based strategies. In previous versions of the toolkit the dictionary-based strategy was only used for translating monosemous English variants. In the experiments we have used Omegawiki and Wiktionary and we present automatic evaluation results for 24 languages that have wordnets in the Open Multilingual Wordnet project. We have used these existing versions of the wordnet to perform an automatic evaluation.
A language-independent LESK based approach to Word Sense Disambiguation (2016)

This paper describes a language- independent LESK based approach to Word Sense Disambiguation (WSD), involving also Vector Space Models applied to the Distributional Semantics Hypotesis. In particular this approach tries to solve some issues that come up with less-resourced languages. The approach also addresses the inadequacy of the Most Frequent Sense (MFS) heuristics to fit specific domain corpora.
plWordNet in Word Sense Disambiguation task (2016)

The paper explores the application of plWordNet, a very large wordnet of Polish, in weakly supervised Word Sense Disambiguation (WSD). Because plWordNet provides only partial descriptions by glosses and usage examples, and does not include sense-disambiguated glosses, PageRank-based WSD methods perform slightly worse than for English. However, we show that the use of weights for the relation types and the order in which lexical units have been added for sense re-ranking can significantly improve WSD precision. The evaluation was done on two Polish corpora (KPWr and Sk{\l}adnica) including manual WSD. We discuss the fundamental difference in the construction of both corpora and very different test results.
plWordNet 3.0 -- Almost There (2016)

It took us nearly ten years to get from no wordnet for Polish to the largest wordnet ever built. We started small but quickly learned to dream big. Now we are about to release plWordNet 3.0-emo {--} complete with sentiment and emotions annotated {--} and a domestic version of Princeton WordNet, larger than WordNet 3.1 by nearly ten thousand newly added words. The paper retraces the road we travelled and talks a little about the future.
Open Dutch WordNet (2016)

We describe Open Dutch WordNet, which has been derived from the Cornetto database, the Princeton WordNet and open source resources. We exploited existing equivalence relations between Cornetto synsets and WordNet synsets in order to move the open source content from Cornetto into WordNet synsets. Currently, Open Dutch Wordnet contains 117,914 synsets, of which 51,588 synsets contain at least one Dutch synonym, which leaves 66,326 synsets still to obtain a Dutch synonym. The average polysemy is 1.5. The resource is currently delivered in XML under the CC BY-SA 4.0 license1 and it has been linked to the Global Wordnet Grid. In order to use the resource, we refer to: https: //github.com/MartenPostma/OpenDutchWordnet.
Verifying Integrity Constraints of a RDF-based WordNet (2016)

This paper presents our first attempt at verifying integrity constraints of our openWordnet-PT against the ontology for Wordnets encoding. Our wordnet is distributed in Resource Description Format (RDF) and we want to guarantee not only the syntax correctness but also its semantics soundness.
DEBVisDic: Instant Wordnet Building (2016)

The semantic network editor DEBVisDic has been used by different development teams to create more than 20 national wordnets. The editor was recently re-developed as a multi-platform web-based application for general semantic networks editing. One of the main advantages, when compared to the previous implementation, lies in the fact that no client-side installation is needed now. Following the successful first phase in building the Open Dutch Wordnet, DEBVisDic was extended with features that allow users to easily create, edit, and share a new (usually national) wordnet without the need of any complicated configuration or advanced technical skills. The DEBVisDic editor provides advanced features for wordnet browsing, editing, and visualization. Apart from the user-friendly web-based application, DEBVisDic also provides an API interface to integrate the semantic network data into external applications.
Sam\=asa-Kart\=a: An Online Tool for Producing Compound Words using IndoWordNet (2016)

Sam{\={a}}sa or compounds are a regular feature of Indian Languages. They are also found in other languages like German, Italian, French, Russian, Spanish, etc. Compound word is constructed from two or more words to form a single word. The meaning of this word is derived from each of the individual words of the compound. To develop a system to generate, identify and interpret compounds, is an important task in Natural Language Processing. This paper introduces a web based tool - Sam{\={a}}sa-Kart{\={a}} for producing compound words. Here, the focus is on Sanskrit language due to its richness in usage of compounds; however, this approach can be applied to any Indian language as well as other languages. IndoWordNet is used as a resource for words to be compounded. The motivation behind creating compound words is to create, to improve the vocabulary, to reduce sense ambiguity, etc. in order to enrich the WordNet. The Sam{\={a}}sa-Kart{\={a}} can be used for various applications viz., compound categorization, sandhi creation, morphological analysis, paraphrasing, synset creation, etc.
Arabic WordNet: New Content and New Applications (2016)

The Arabic WordNet project has provided the Arabic Natural Language Processing (NLP) community with the first WordNet-compliant resource. It allowed new possibilities in terms of building sophisticated NLP applications related to this Semitic language. In this paper, we present the new content added to this resource, using semi-automatic techniques, and validated by Arabic native-speaker lexicographers. We also present how this content helps in the implementation of new Arabic NLP applications, especially for Question Answering (QA) systems. The obtained results show the contribution of the added content. The resource, fully transformed into the standard Lexical Markup Framework (LMF), is made available for the community.
Hydra for Web: A Browser for Easy Access to Wordnets (2016)

This paper presents a web interface for wordnets named Hydra for Web which is built on top of Hydra {--} an open source tool for wordnet development {--} by means of modern web technologies. It is a Single Page Application with simple but powerful and convenient GUI. It has two modes for visualisation of the language correspondences of searched (and found) wordnet synsets {--} single and parallel modes. Hydra for web is available at: \url{http://dcl.bas.bg/bulnet/}.
Towards a methodology for filtering out gaps and mismatches across wordnets: the case of plWordNet and Princeton WordNet (2016)

This paper presents the results of large-scale noun synset mapping between plWordNet, the wordnet of Polish, and Princeton WordNet, the wordnet of English, which have shown high predominance of inter-lingual hyponymy relation over inter-synonymy relation. Two main sources of such effect are identified in the paper: differences in the methodologies of construction of plWN and PWN and cross-linguistic differences in lexicalization of concepts and grammatical categories between English and Polish. Next, we propose a typology of specific gaps and mismatches across wordnets and a rule-based system of filters developed specifically to scan all I(inter-lingual)-hyponymy links between plWN and PWN. The proposed system, it should be stressed, also enables one to pinpoint the frequencies of the identified gaps and mismatches.
Folktale similarity based on ontological abstraction (2016)

This paper presents a method to compute similarity of folktales based on conceptual overlap at various levels of abstraction as defined in Dutch WordNet. The method is applied on a corpus of Dutch folktales and evaluated using a comparison to traditional folktale similarity analysis based on the Aarne{--}Thompson{--}Uther (ATU) classification system. Document similarity computed by the presented method is in agreement with traditional analysis for a certain amount of folktale pairs, but differs for other pairs. However, it can be argued that the current approach computes an alternative, data-driven type of similarity. Using WordNet instead of a domain-specific ontology or classification system ensures applicability of the method outside of the folktale domain.
The Predicate Matrix and the Event and Implied Situation Ontology: Making More of Events (2016)

This paper presents the Event and Implied Situation Ontology (ESO), a resource which formalizes the pre and post situations of events and the roles of the entities affected by an event. The ontology reuses and maps across existing resources such as WordNet, SUMO, VerbNet, PropBank and FrameNet. We describe how ESO is injected into a new version of the Predicate Matrix and illustrate how these resources are used to detect information in large document collections that otherwise would have remained implicit. The model targets interpretations of situations rather than the semantics of verbs per se. The event is interpreted as a situation using RDF taking all event components into account. Hence, the ontology and the linked resources need to be considered from the perspective of this interpretation model.
Semi-Automatic Mapping of WordNet to Basic Formal Ontology (2016)

We present preliminary work on the mapping of WordNet 3.0 to the Basic Formal Ontology (BFO 2.0). WordNet is a large, widely used semantic network. BFO is a domain-neutral upper-level ontology that represents the types of things that exist in the world and relations between them. BFO serves as an integration hub for more specific ontologies, such as the Ontology for Biomedical Investigations (OBI) and Ontology for Biobanking (OBIB). This work aims at creating a lexico-semantic resource that can be used in NLP tools to perform ontology-related text manipulation tasks. Our semi-automatic mapping method consists in using existing mappings between WordNet and the KYOTO Ontology. The latter allows machines to reason over texts by providing interpretations of the words in ontological terms. Our working hypothesis is that a large portion of WordNet synsets can be semi-automatically mapped to BFO using simple mapping rules from KYOTO to BFO. We evaluate the method on a randomized subset of synsets, examine preliminary results, and discuss challenges related to the method. We conclude with suggestions for future work.
Augmenting FarsNet with New Relations and Structures for verbs (2016)

This paper discusses the semantic augmentation of FarsNet - the Persian WordNet - with new relations and structures for verbs. FarsNet1.0, the first Persian WordNet obeys the Structure of Princeton WordNet 2.1. In this paper we discuss FarsNet 2.0 in which new inter-POS relations and verb frames are added. In fact FarsNet2.0 is a combination of WordNet and VerbNet for Persian. It includes more than 30,000 lexical entries arranged in about 20,000 synsets with about 18000 mappings to Princeton WordNet synsets. There ae about 43000 relations between synsets and senses in FarsNet 2.0. It includes verb frames in two levels (syntactic and thematic) for about 200 simple Persian verbs.
High, Medium or Low? Detecting Intensity Variation Among polar synonyms in WordNet (2016)

For fine-grained sentiment analysis, we need to go beyond zero-one polarity and find a way to compare adjectives (synonyms) that share the same sense. Choice of a word from a set of synonyms, provides a way to select the exact polarity-intensity. For example, choosing to describe a person as benevolent rather than kind1 changes the intensity of the expression. In this paper, we present a sense based lexical resource, where synonyms are assigned intensity levels, viz., high, medium and low. We show that the measure P (s|w) (probability of a sense s given the word w) can derive the intensity of a word within the sense. We observe a statistically significant positive correlation between P(s|w) and intensity of synonyms for three languages, viz., English, Marathi and Hindi. The average correlation scores are 0.47 for English, 0.56 for Marathi and 0.58 for Hindi.
The Role of the WordNet Relations in the Knowledge-based Word Sense Disambiguation Task (2016)

In this paper we present an analysis of different semantic relations extracted from WordNet, Extended WordNet and SemCor, with respect to their role in the task of knowledge-based word sense disambiguation. The experiments use the same algorithm and the same test sets, but different variants of the knowledge graph. The results show that different sets of relations have different impact on the results: positive or negative. The beneficial ones are discussed with respect to the combination of relations and with respect to the test set. The inclusion of inference has only a modest impact on accuracy, while the addition of syntactic relations produces stable improvement over the baselines.
Detection of Compound Nouns and Light Verb Constructions using IndoWordNet (2016)

Detection of MultiWord Expressions (MWEs) is one of the fundamental problems in Natural Language Processing. In this paper, we focus on two categories of MWEs - Compound Nouns and Light Verb Constructions. These two categories can be tackled using knowledge bases, rather than pure statistics. We investigate usability of IndoWordNet for the detection of MWEs. Our IndoWordNet based approach uses semantic and ontological features of words that can be extracted from IndoWordNet. This approach has been tested on Indian languages viz., Assamese, Bengali, Hindi, Konkani, Marathi, Odia and Punjabi. Results show that ontological features are found to be very useful for the detection of light verb constructions, while use of semantic properties for the detection of compound nouns is found to be satisfactory. This approach can be easily adapted by other Indian languages. Detected MWEs can be interpolated into WordNets as they help in representing semantic knowledge.
Mapping it differently: A solution to the linking challenges (2016)

This paper reports the work of creating bilingual mappings in English for certain synsets of Hindi wordnet, the need for doing this, the methods adopted and the tools created for the task. Hindi wordnet, which forms the foundation for other Indian language wordnets, has been linked to the English WordNet. To maximize linkages, an important strategy of using direct and hypernymy linkages has been followed. However, the hypernymy linkages were found to be inadequate in certain cases and posed a challenge due to sense granularity of language. Thus, the idea of creating bilingual mappings was adopted as a solution. A bilingual mapping means a linkage between a concept in two different languages, with the help of translation and/or transliteration. Such mappings retain meaningful representations, while capturing semantic similarity at the same time. This has also proven to be a great enhancement of Hindi wordnet and can be a crucial resource for multilingual applications in natural language processing, including machine translation and cross language information retrieval.
WordNet-based similarity metrics for adjectives (2016)

Le and Fokkens (2015) recently showed that taxonomy-based approaches are more reliable than corpus-based approaches in estimating human similarity ratings. On the other hand, distributional models provide much better coverage. The lack of an established similarity metric for adjectives in WordNet is a case in point. I present initial work to establish such a metric, and propose ways to move forward by looking at extensions to WordNet. I show that the shortest path distance between derivationally related forms provides a reliable estimate of adjective similarity. Furthermore, I find that a hybrid method combining this measure with vector-based similarity estimations gives us the best of both worlds: more reliable similarity estimations than vectors alone, but with the same coverage as corpus-based methods.
Toward a truly multilingual GlobalWordnet Grid (2016)

In this paper, we describe a new and improved Global Wordnet Grid that takes advantage of the Collaborative InterLingual Index (CILI). Currently, the Open Multilingal Wordnet has made many wordnets accessible as a single linked wordnet, but as it used the Princeton Wordnet of English (PWN) as a pivot, it loses concepts that are not part of PWN. The technical solution to this, a central registry of concepts, as proposed in the EuroWordnet project through the InterLingual Index, has been known for many years. However, the practical issues of how to host this index and who decides what goes in remained unsolved. Inspired by current practice in the Semantic Web and the Linked Open Data community, we propose a way to solve this issue. In this paper we define the principles and protocols for contributing to the Grid. We tested them on two use cases, adding version 3.1 of the Princeton WordNet to a CILI based on 3.0 and adding the Open Dutch Wordnet, to validate the current set up. This paper aims to be a call for action that we hope will be further discussed and ultimately taken up by the whole wordnet community.
This Table is Different: A WordNet-Based Approach to Identifying References to Document Entities (2016)

Writing intended to inform frequently contains references to document entities (DEs), a mixed class that includes orthographically structured items (e.g., illustrations, sections, lists) and discourse entities (arguments, suggestions, points). Such references are vital to the interpretation of documents, but they often eschew identifiers such as {\textquotedblleft}Figure 1{\textquotedblright} for inexplicit phrases like {\textquotedblleft}in this figure{\textquotedblright} or {\textquotedblleft}from these premises{\textquotedblright}. We examine inexplicit references to DEs, termed DE references, and recast the problem of their automatic detection into the determination of relevant word senses. We then show the feasibility of machine learning for the detection of DE-relevant word senses, using a corpus of human-labeled synsets from WordNet. We test cross-domain performance by gathering lemmas and synsets from three corpora: website privacy policies, Wikipedia articles, and Wikibooks textbooks. Identifying DE references will enable language technologies to use the information encoded by them, permitting the automatic generation of finely-tuned descriptions of DEs and the presentation of richly-structured information to readers.
WordNet and beyond: the case of lexical access (2016)

For humans the main functions of a dictionary is to store information concerning words and to reveal it when needed. While readers are interested in the meaning of words, writers look for answers concerning usage, spelling, grammar or word forms (lemma). We will focus here on this latter task: help authors to find the word they are looking for, word they may know but whose form is eluding them. Put differently, we try to build a resource helping authors to overcome the tip-of-the-tongue problem (ToT). Obviously, in order to access a word, it must be stored somewhere (brain, resource). Yet this is by no means sufficient. We will illustrate this here by comparing WordNet (WN) to an equivalent lexical resource bootstrapped from Wikipedia (WiPi). Both may contain a given word, but ease and success of access may be different depending on other factors like quality of the query, proximity, type of connections, etc. Next we will show under what conditions WN is suitable for word access, and finally we will present a roadmap showing the obstacles to be overcome to build a resource allowing the text producer to find the word s/he is looking for.
How to Differentiate the Closely Related Standard Languages? (2016)

In this paper the adequacy of the SETimes corpus as a basis for the comparison of closely related languages that are used in countries that emerged after the breakup of Yugoslavia is discussed by comparing it with other corpora. It is shown that the phenomena observed in this corpus and used to illustrate differences most specifically between Serbian and Croatian are consistent neither with their standards nor with other sources. Thus, results obtained on the basis of the SETimes corpus are corpus-biased and have to be reconsidered. This proves that the size of a corpus and its composition used in a linguistic research are crucial for assessing the obtained results.
`While' and `Until' Clauses and Expletive Negation in a Corpus of Bulgarian and Ukrainian Parallel Texts (2016)

The combination of the meanings {\textquoteleft}while' and {\textquoteleft}until' in a single lexeme and the use of expletive negation with the latter meaning are widespread phenomena that are a rich source of research problems. In this paper we present a comparative bilingual Bulgarian and Ukrainian corpus-based study of several conjunctions that share these two meanings. We discuss the difference in the frequency of expletive negation in the two languages, the use of a{\v{z}} {\textquoteleft}even, all the way' in Ukrainian and the impact of the original language in translated texts.
Linguistic Data Retrievable from a Treebank (2016)

This paper describes the Romanian treebank annotated according to the Universal Dependency principles. We present the types of texts included in the treebank, their processing phases and the tools used for doing it, as well as the levels of annotation, with a focus on the syntactic level. We briefly present the syntactic formalism used, the principles followed and the set of relations. The perspective we adopted is the linguist`s who searches the treebank for information with relevance for the study of Romanian. (S)He can interpret the statistics based on the corpus and can also query the treebank for finding examples to support a theory, for testing hypothesis or for discovering new tendencies. We use here the passive constructions in Romanian as a case study for showing how statistical data help understanding this linguistic phenomenon. We also discuss the kinds of linguistic information retrievable and non-retrievable form the treebank, based on the annotation principles.