ymoslem/acl-abstracts huggingface dataset:
Synthetic, yet natural: Properties of WordNet random walk corpora and the impact of rare words on embedding performance (2019)

Creating word embeddings that reflect semantic relationships encoded in lexical knowledge resources is an open challenge. One approach is to use a random walk over a knowledge graph to generate a pseudo-corpus and use this corpus to train embeddings. However, the effect of the shape of the knowledge graph on the generated pseudo-corpora, and on the resulting word embeddings, has not been studied. To explore this, we use English WordNet, constrained to the taxonomic (tree-like) portion of the graph, as a case study. We investigate the properties of the generated pseudo-corpora, and their impact on the resulting embeddings. We find that the distributions in the psuedo-corpora exhibit properties found in natural corpora, such as Zipf`s and Heaps' law, and also observe that the proportion of rare words in a pseudo-corpus affects the performance of its embeddings on word similarity.
Augmenting Chinese WordNet semantic relations with contextualized embeddings (2019)

Constructing semantic relations in WordNet has been a labour-intensive task, especially in a dynamic and fast-changing language environment. Combined with recent advancements of contextualized embeddings, this paper proposes the concept of morphology-guided sense vectors, which can be used to semi-automatically augment semantic relations in Chinese Wordnet (CWN). This paper (1) built sense vectors with pre-trained contextualized embedding models; (2) demonstrated the sense vectors computed were consistent with the sense distinctions made in CWN; and (3) predicted the potential semantically-related sense pairs with high accuracy by sense vectors model.
Visualising WordNet Embeddings: some preliminary results (2019)

AutoExtend is a method for learning unambiguous vector embeddings for word senses. We visualise these word embeddings with t-SNE, which further compresses the vectors to the x,y plane. We show that the t-SNE co-ordinates can be used to reveal interesting semantic relations between word senses, and propose a new method that uses the simple x,y coordinates to compute semantic similarity. This can be used to propose new links and alterations to existing ones in WordNet. We plan to add this approach to the existing toolbox of methods in an attempt to understand learned semantic relations in word embeddings.
The Making of Coptic Wordnet (2019)

With the increasing availability of wordnets for ancient languages, such as Ancient Greek and Latin, gaps remain in the coverage of less studied languages of antiquity. This paper reports on the construction and evaluation of a new wordnet for Coptic, the language of Late Roman, Byzantine and Early Islamic Egypt in the first millenium CE. We present our approach to constructing the wordnet which uses multilingual Coptic dictionaries and wordnets for five different languages. We further discuss the results of this effort and outline our on-going/future work.
Evaluating the Wordnet and CoRoLa-based Word Embedding Vectors for Romanian as Resources in the Task of Microworlds Lexicon Expansion (2019)

Within a larger frame of facilitating human-robot interaction, we present here the creation of a core vocabulary to be learned by a robot. It is extracted from two tokenised and lemmatized scenarios pertaining to two imagined microworlds in which the robot is supposed to play an assistive role. We also evaluate two resources for their utility for expanding this vocabulary so as to better cope with the robot`s communication needs. The language under study is Romanian and the resources used are the Romanian wordnet and word embedding vectors extracted from the large representative corpus of contemporary Romanian, CoRoLa. The evaluation is made for two situations: one in which the words are not semantically disambiguated before expanding the lexicon, and another one in which they are disambiguated with senses from the Romanian wordnet. The appropriateness of each resource is discussed.
Towards linking synonymous expressions of compound verbs to Japanese WordNet (2019)

This paper describes our project on Japanese compound verbs. Japanese {\textquotedblleft}Verb (adnominal form) + Verb{\textquotedblright} compounds, which are treated as single verbs, frequently appear in daily communication. They are not sufficiently registered in Japanese dictionaries or thesauri. We are now compiling a list of the synonymous expressions of compound verbs in {\textquotedblleft}compound verb lexicon{\textquotedblright} built by the National Institute of Japanese Language and Linguistics. We extracted synonymous words and phrases of compound verbs from five hundred million Japanese web corpora. As a result, synonymous expressions of 1800 compound verbs were obtained automatically among 2700 in the {\textquotedblleft}compound verb lexicon{\textquotedblright}. From our data, we observed that some compound verbs represent not only motion but also additional nuances such as an emotional one. In order to reflect the abundant meanings that compound verbs own, we will try to think of a link of synonymous expressions to Japanese wordnet. Concretely, in the case of synonymous phrases, we try to link adverbial expressions which are a part of phrases to the adverbial synset in Japanese wordnet.
Thinking globally, acting locally -- Progress in the African Wordnet Project (2019)

The African Wordnet Project (AWN) includes all nine indigenous South African languages, namely isiZulu, isiXhosa, Setswana, Sesotho sa Leboa, Tshivenda, Siswati, Sesotho, isiNdebele and Xitsonga. The AWN currently includes 61 000 synsets as well as definitions and usage examples for a large part of the synsets. The project recently received extended funding from the South African Centre for Digital Language Resources (SADiLaR) and aims to update all aspects of the current resource, including the seed list used for new development, software tools used and mapping the AWN to the latest version of PWN 3.1. As with any resource development project, it is essential to also include phases of focused quality assurance and updating of the basis on which the resource is built. The African languages remain under-resourced. This paper describes progress made in the development of the AWN as well as recent technical improvements.
Commonsense Reasoning Using WordNet and SUMO: a Detailed Analysis (2019)

We describe a detailed analysis of a sample of large benchmark of commonsense reasoning problems that has been automatically obtained from WordNet, SUMO and their mapping. The objective is to provide a better assessment of the quality of both the benchmark and the involved knowledge resources for advanced commonsense reasoning tasks. By means of this analysis, we are able to detect some knowledge misalignments, mapping errors and lack of knowledge and resources. Our final objective is the extraction of some guidelines towards a better exploitation of this commonsense knowledge framework by the improvement of the included resources.
Building the Cantonese Wordnet (2019)

This paper reports on the development of the Cantonese Wordnet, a new wordnet project based on Hong Kong Cantonese. It is built using the expansion approach, leveraging on the existing Chinese Open Wordnet, and the Princeton Wordnet`s semantic hierarchy. The main goal of our project was to produce a high quality, human-curated resource {--} and this paper reports on the initial efforts and steady progress of our building method. It is our belief that the lexical data made available by this wordnet, including Jyutping romanization, will be useful for a variety of future uses, including many language processing tasks and linguistic research on Cantonese and its interactions with other Chinese dialects.
Deep Learning in Event Detection in Polish (2019)

Event detection is an important NLP task that has been only recently tackled in the context of Polish, mostly due to lack of language resources. The available annotated corpora are still relatively small and supervised learning approaches are limited by the size of training datasets. Event detection tools are very much needed, as they can be used to annotate more language resources automatically and to improve the accuracy of other NLP tasks, which rely on the detection of events, such as question answering or machine translation. In this paper we present a deep learning based approach to this task, which proved to capture the knowledge contained in the training data most effectively and outperform previously proposed methods. We show a direct comparison to previously published results, using the same data and experimental setup.
Textual genre based approach to use WordNet in language-for-specific-purpose classroom as dictionary (2019)

When teaching language for specific purposes (LSP) linguistic resources are needed to help students understand and write specialised texts. As building a lexical resource is costly, we explore the use of wordnets to represent the terms that can be found in particular textual domains. In order to gather the terms to be included in wordnets, we propose a textual genre approach, that leads us to introduce a new relation term used in to link all the possible terms/synsets that can appear in a text to the synset of the textual genre. This way, students can use wordnet as dictionary or thesaurus when writing specialised texts. We explain our approach by means of the logbooks and terms in Basque. A side effect of this works is also enriching the wordnets with new variants and synsets.
Fitting Semantic Relations to Word Embeddings (2019)

We fit WordNet relations to word embeddings, using 3CosAvg and LRCos, two set-based methods for analogy resolution, and introduce 3CosWeight, a new, weighted variant of 3CosAvg. We test the performance of the resulting semantic vectors in lexicographic semantics tests, and show that none of the tested classifiers can learn symmetric relations like synonymy and antonymy, since the source and target words of these relations are the same set. By contrast, with the asymmetric relations (hyperonymy / hyponymy and meronymy), both 3CosAvg and LRCos clearly outperform the baseline in all cases, while 3CosWeight attained the best scores with hyponymy and meronymy, suggesting that this new method could provide a useful alternative to previous approaches.
Building the Mongolian WordNet (2019)

This paper presents the Mongolian Wordnet (MOW), and a general methodology of how to construct it from various sources e.g. lexical resources and expert translations. As of today, the MOW contains 23,665 synsets, 26,875 words, 2,979 glosses, and 213 examples. The manual evaluation of the resource1 estimated its quality at 96.4{\%}.
English WordNet 2019 -- An Open-Source WordNet for English (2019)

We describe the release of a new wordnet for English based on the Princeton WordNet, but now developed under an open-source model. In particular, this version of WordNet, which we call English WordNet 2019, which has been developed by multiple people around the world through GitHub, fixes many errors in previous wordnets for English. We give some details of the changes that have been made in this version and give some perspectives about likely future changes that will be made as this project continues to evolve.
Assessing Wordnets with WordNet Embeddings (2019)

An effective conversion method was proposed in the literature to obtain a lexical semantic space from a lexical semantic graph, thus permitting to obtain WordNet embeddings from WordNets. In this paper, we propose the exploitation of this conversion methodology as the basis for the comparative assessment of WordNets: given two WordNets, their relative quality in terms of capturing the lexical semantics of a given language, can be assessed by (i) converting each WordNet into the corresponding semantic space (i.e. into WordNet embeddings), (ii) evaluating the resulting WordNet embeddings under the typical semantic similarity prediction task used to evaluate word embeddings in general; and (iii) comparing the performance in that task of the two word embeddings, extracted from the two WordNets. A better performance in that evaluation task results from the word embeddings that are better at capturing the semantic similarity of words, which, in turn, result from the WordNet that is of higher quality at capturing the semantics of words.
Spoken WordNet (2019)

WordNets have been used in a wide variety of applications, including in design and development of intelligent and human assisting systems. Although WordNet was initially developed as an online lexical database, (Miller, 1995 and Fellbaum, 1998) later developments have inspired using WordNet database as resources in NLP applications, Language Technology developments, and as sources of structured learned materials. This paper proposes, conceptualizes, designs, and develops a voice enabled information retrieval system, facilitating WordNet knowledge presentation in a spoken format, based on a spoken query. In practice, the work converts the WordNet resource into a structured voiced based knowledge extraction system, where a spoken query is processed in a pipeline, and then extracting the relevant WordNet resources, structuring through another process pipeline, and then presented in spoken format. Thus the system facilitates a speech interface to the existing WordNet and we named the system as {\textquotedblleft}Spoken WordNet{\textquotedblright}. The system interacts with two interfaces, one designed and developed for Web, and the other as an App interface for smartphone. This is also a kind of restructuring the WordNet as a friendly version for visually challenged users. User can input query string in the form of spoken English sentence or word. Jaccard Similarity is calculated between the input sentence and the synset definitions. The one with highest similarity score is taken as the synset of interest among multiple available synsets. User is also prompted to choose a contextual synset, in case of ambiguities.
OntoLex as a possible Bridge between WordNets and full lexical Descriptions (2019)

In this paper we describe our current work on representing a recently created German lexical semantics resource in OntoLex-Lemon and in conformance with WordNet specifications. Besides presenting the representation effort, we show the utilization of OntoLex-Lemon to bridge from WordNet-like resources to full lexical descriptions and extend the coverage of WordNets to other types of lexical data, such as decomposition results, exemplified for German data, and inflectional phenomena, here outlined for English data.
Semi-automatic Annotation of Event Structure, Argument Structure, and Opposition Structure to WordNet by Using Event Structure Frame (2019)

In this paper, we present semi-automatic annotation of the Event Structure Frames to synsets of English verbs in WordNet. The Event Structure Frame is a sub-eventual structure frame which combines event structure (lexical aspect) with argument structure represented by semantic roles and opposition structure which represents the presupposed and entailed sub-events of a matrix event. Our annotation work is done semi-automatically by GESL-based automatic annotation and manual error-correction. GESL is an automatic annotation tool of the Event Structure Frame to verbs in a sentence. We apply GESL to the example sentence given for each synset of a verb in WordNet. We expect that our work will make WordNet much more useful for any NLP and its applications which require lexical semantic information of English verbs.
Enhancing Conceptual Description through Resource Linking and Exploration of Semantic Relations (2019)

The paper presents current efforts towards linking two large lexical semantic resources {--} WordNet and FrameNet {--} to the end of their mutual enrichment and the facilitation of the access, extraction and analysis of various types of semantic and syntactic information. In the second part of the paper, we go on to examine the relation of inheritance and other semantic relations as represented in WordNet and FrameNet and how they correspond to each other when the resources are aligned. We discuss the implications with respect to the enhancement of the two resources through the definition of new relations and the detailisation of conceptual frames.
Aligning the Bulgarian BTB WordNet with the Bulgarian Wikipedia (2019)

The paper reports on an ongoing work that manually maps the Bulgarian WordNet BTB-WN with Bulgarian Wikipedia. The preparatory work of extracting the Wikipedia articles and provisionally relating them to the WordNet lemmas was done automatically. The manual work includes checking of the corresponding senses in both resources as well as the missing ones. The main cases of mapping are considered. The first experiments of mapping about 1000 synsets show the establishment of more than 78 {\%} of exact correspondences and nearly 15 {\%} of new synsets.
English-Turkish Parallel Semantic Annotation of Penn-Treebank (2019)

This paper reports our efforts in constructing a sense-labeled English-Turkish parallel corpus using the traditional method of manual tagging. We tagged a pre-built parallel treebank which was translated from the Penn Treebank corpus. This approach allowed us to generate a resource combining syntactic and semantic information. We provide statistics about the corpus itself as well as information regarding its development process.
Comparing Sense Categorization Between English PropBank and English WordNet (2019)

Given the fact that verbs play a crucial role in language comprehension, this paper presents a study which compares the verb senses in English PropBank with the ones in English WordNet through manual tagging. After analyzing 1554 senses in 1453 distinct verbs, we have found out that while the majority of the senses in PropBank have their one-to-one correspondents in WordNet, a substantial amount of them are differentiated. Furthermore, by analysing the differences between our manually-tagged and an automatically-tagged resource, we claim that manual tagging can help provide better results in sense annotation.
Building ASLNet, a Wordnet for American Sign Language (2019)

We discuss the creation of ASLNet by aligning the Princeton WordNet (PWN) with SignStudy, an online database of American Sign Language (ASL) signs. This alignment will have many immediate benefits for first and second-sign language learners as well as ASL researchers by highlighting semantic relations among signs. We begin to address the interesting theoretical question of to what extent the wordnet-style organization of the English lexicon (and those of wordnets in other spoken languages) is applicable to ASL, and whether ASL requires positing additional, language or modality-specific relations among signs. Significantly, the mapping of SignStudy and PWN provides a bridge between ASL and the worldwide wordnet community, which comprises speakers of dozens of languages working in academic and language technology settings.
A collaborative system for building and maintaining wordnets. (2019)

A collaborative system for wordnet construction and maintenance is presented. Its key modules include WordnetLoom editor, Wordnet Tracker and JavaScript Graph. They offer a number of functionalities that allow solving problems on every stage of building, editing and aligning wordnets by teams of lexicographers working in parallel. The experience collected in recent years has allowed us to refine applications and add new modules to provide the best user experience in a reliable and easily maintainable way.
Enriching Keywords Database UsingWordnets -- a Case Study (2019)

In the paper, we study the case of building a keywords database related to the Polish Classification of Activities (PKD 2007). The database enables automatic classification of the companies to the industry branches. The classification is performed based on the company`s activity description. We present the initial design of the keywords database and the ways in which wordnets were used to enrich it. Finally, we present the preliminary statistical evaluation of the produced resource.
Propagation of emotions, arousal and polarity in WordNet using Heterogeneous Structured Synset Embeddings (2019)

In this paper we present a novel method for emotive propagation in a wordnet based on a large emotive seed. We introduce a sense-level emotive lexicon annotated with polarity, arousal and emotions. The data were annotated as a part of a large study involving over 20,000 participants. A total of 30,000 lexical units in Polish WordNet were described with metadata, each unit received about 50 annotations concerning polarity, arousal and 8 basic emotions, marked on a multilevel scale. We present a preliminary approach to propagating emotive metadata to unlabeled lexical units based on the distribution of manual annotations using logistic regression and description of mixed synset embeddings based on our Heterogeneous Structured Synset Embeddings.
Testing Zipf`s meaning-frequency law with wordnets as sense inventories (2019)

According to George K. Zipf, more frequent words have more senses. We have tested this law using corpora and wordnets of English, Spanish, Portuguese, French, Polish, Japanese, Indonesian and Chinese. We have proved that the law works pretty well for all of these languages if we take - as Zipf did - mean values of meaning count and averaged ranks. On the other hand, the law disastrously fails in predicting the number of senses for a single lemma. We have also provided the evidence that slope coefficients of Zipfian log-log linear model may vary from language to language.
plWordNet 4.1 - a Linguistically Motivated, Corpus-based Bilingual Resource (2019)

The paper presents the latest release of the Polish WordNet, namely plWordNet 4.1. The most significant developments since 3.0 version include new relations for nouns and verbs, mapping semantic role-relations from the valency lexicon Walenty onto the plWordNet structure and sense-level inter-lingual mapping. Several statistics are presented in order to illustrate the development and contemporary state of the wordnet.
A Comparison of Sense-level Sentiment Scores (2019)

In this paper, we compare a variety of sense-tagged sentiment resources, including SentiWordNet, ML-Senticon, plWordNet emo and the NTU Multilingual Corpus. The goal is to investigate the quality of the resources and see how well the sentiment polarity annotation maps across languages.
Portuguese Manners of Speaking (2019)

Lexical resources need to be as complete as possible. Very little work seems to have been done on adverbs, the smallest part of speech class in Princeton WordNet counting the number of synsets. Amongst adverbs, manner adverbs ending in {\textquoteleft}-ly' seem the easiest to work with, as their meaning is almost the same as the one of the associated adjective. This phenomenon seems to be parallel in English and Portuguese, where these manner adverbs finish in the suffix {\textquoteleft}-mente'. We use this correspondence to improve the coverage of adverbs in the lexical resource OpenWordNet-PT, a wordnet for Portuguese.
Completing the Princeton Annotated Gloss Corpus Project (2019)

In the Princeton WordNet Gloss Corpus, the word forms from the definitions ({\textquotedblleft}glosses{\textquotedblright}) in WordNet`s synsets are manually linked to the context-appropriate sense in the WordNet. The glosses then become a sense-disambiguated corpus annotated against WordNet version 3.0. The result is also called a semantic concordance, which can be seen as both a lexicon (WordNet extension) and an annotated corpus. In this work we motivate and present the initial steps to complete the annotation of all open-class words in this corpus. Finally, we introduce a freely-available annotation interface built as an Emacs extension, and evaluate a preliminary annotation effort.