pwc-archive/papers-with-abstracts huggingface dataset:
Towards a Semi-Automatic Detection of Reflexive and Reciprocal Constructions and Their Representation in a Valency Lexicon
Authors: V{\'a}clava Kettnerov{\'a}, Marketa Lopatkova, Anna Vernerov{\'a}, Petra Barancikova
Date: 2020-05-01 00:00:00
Proceeding: LREC 2020 5
Tasks: Word Embeddings

Valency lexicons usually describe valency behavior of verbs in non-reflexive and non-reciprocal constructions. However, reflexive and reciprocal constructions are common morphosyntactic forms of verbs. Both of these constructions are characterized by regular changes in morphosyntactic properties of verbs, thus they can be described by grammatical rules. On the other hand, the possibility to create reflexive and/or reciprocal constructions cannot be trivially derived from the morphosyntactic structure of verbs as it is conditioned by their semantic properties as well. A large-coverage valency lexicon allowing for rule based generation of all well formed verb constructions should thus integrate the information on reflexivity and reciprocity. In this paper, we propose a semi-automatic procedure, based on grammatical constraints on reflexivity and reciprocity, detecting those verbs that form reflexive and reciprocal constructions in corpus data. However, exploitation of corpus data for this purpose is complicated due to the diverse functions of reflexive markers crossing the domain of reflexivity and reciprocity. The list of verbs identified by the previous procedure is thus further used in an automatic experiment, applying word embeddings for detecting semantically similar verbs. These candidate verbs have been manually verified and annotation of their reflexive and reciprocal constructions has been integrated into the valency lexicon of Czech verbs VALLEX.
Languages Resources for Poorly Endowed Languages : The Case Study of Classical Armenian
Authors: Chahan Vidal-Gor{\`e}ne, Ali{\'e}nor Decours-Perez
Date: 2020-05-01 00:00:00
Proceeding: LREC 2020 5

Classical Armenian is a poorly endowed language, that despite a great tradition of lexicographical erudition is coping with a lack of resources. Although numerous initiatives exist to preserve the Classical Armenian language, the lack of precise and complete grammatical and lexicographical resources remains. This article offers a situation analysis of the existing resources for Classical Armenian and presents the new digital resources provided on the Calfa platform. The Calfa project gathers existing resources and updates, enriches and enhances their content to offer the richest database for Classical Armenian today. Faced with the challenges specific to a poorly endowed language, the Calfa project is also developing new technologies and solutions to enable preservation, advanced research, and larger systems and developments for the Armenian language
Constructing Web-Accessible Semantic Role Labels and Frames for Japanese as Additions to the NPCMJ Parsed Corpus
Authors: Koichi Takeuchi, Alastair Butler, Iku Nagasaki, Takuya Okamura, Prashant Pardeshi
Date: 2020-05-01 00:00:00
Proceeding: LREC 2020 5
Tasks: AMR Parsing, Semantic Parsing

As part of constructing the NINJAL Parsed Corpus of Modern Japanese (NPCMJ), a web-accessible language resource, we are adding frame information for predicates, together with two types of semantic role labels that mark the contributions of arguments. One role type consists of numbered semantic roles, like in PropBank, to capture relations between arguments in different syntactic patterns. The other role type consists of semantic roles with conventional names.Both role types are compatible with hierarchical frames that belong to related predicates. Adding semantic role and frame information to the NPCMJ will support a web environment where language learners and linguists can search examples of Japanese for syntactic and semantic features. The annotation will also provide a language resource for NLP researchers making semantic parsing models (e.g., for AMR parsing) following machine learning approaches. In this paper, we describe how the two types of semantic role labels are defined under the frame based approach, i.e., both types can be consistently applied when linked to corresponding frames. Then we show special cases of syntactic patterns and the current status of the annotation work.
Large-scale Cross-lingual Language Resources for Referencing and Framing
Authors: Piek Vossen, Filip Ilievski, Marten Postma, Antske Fokkens, Gosse Minnema, Levi Remijnse
Date: 2020-05-01 00:00:00
Proceeding: LREC 2020 5

In this article, we lay out the basic ideas and principles of the project Framing Situations in the Dutch Language. We provide our first results of data acquisition, together with the first data release. We introduce the notion of cross-lingual referential corpora. These corpora consist of texts that make reference to exactly the same incidents. The referential grounding allows us to analyze the framing of these incidents in different languages and across different texts. During the project, we will use the automatically generated data to study linguistic framing as a phenomenon, build framing resources such as lexicons and corpora. We expect to capture larger variation in framing compared to traditional approaches for building such resources. Our first data release, which contains structured data about a large number of incidents and reference texts, can be found at http://dutchframenet.nl/data-releases/.
Modelling Etymology in LMF/TEI: The Grande Dicion\'ario Houaiss da L\'\ingua Portuguesa Dictionary as a Use Case
Authors: Fahad Khan, Laurent Romary, Ana Salgado, Jack Bowers, Mohamed Khemakhem, Toma Tasovac
Date: 2020-05-01 00:00:00
Proceeding: LREC 2020 5

In this article we will introduce two of the new parts of the new multi-part version of the Lexical Markup Framework (LMF) ISO standard, namely part 3 of the standard (ISO 24613-3), which deals with etymological and diachronic data, and Part 4 (ISO 24613-4), which consists of a TEI serialisation of all of the prior parts of the model. We will demonstrate the use of both standards by describing the LMF encoding of a small number of examples taken from a sample conversion of the reference Portuguese dictionary \textit{Grande Dicion{\'a}rio Houaiss da L{\'\i}ngua Portuguesa}, part of a broader experiment comprising the analysis of different, heterogeneously encoded, Portuguese lexical resources. We present the examples in the Unified Modelling Language (UML) and also in a couple of cases in TEI.
Linking the TUFS Basic Vocabulary to the Open Multilingual Wordnet
Authors: Francis Bond, Hiroki Nomoto, Lu{\'\i}s Morgado da Costa, Arthur Bond
Date: 2020-05-01 00:00:00
Proceeding: LREC 2020 5
Tasks: LEMMA, Sentence

We describe the linking of the TUFS Basic Vocabulary Modules, created for online language learning, with the Open Multilingual Wordnet. The TUFS modules have roughly 500 lexical entries in 30 languages, each with the lemma, a link across the languages, an example sentence, usage notes and sound files. The Open Multilingual Wordnet has 34 languages (11 shared with TUFS) organized into synsets linked by semantic relations, with examples and definitions for some languages. The links can be used to (i) evaluate existing wordnets, (ii) add data to these wordnets and (iii) create new open wordnets for Khmer, Korean, Lao, Mongolian, Russian, Tagalog, Urdua nd Vietnamese
Some Issues with Building a Multilingual Wordnet
Authors: Francis Bond, Luis Morgado da Costa, Michael Wayne Goodman, John Philip McCrae, Ahti Lohk
Date: 2020-05-01 00:00:00
Proceeding: LREC 2020 5

In this paper we discuss the experience of bringing together over 40 different wordnets. We introduce some extensions to the GWA wordnet LMF format proposed in Vossen et al. (2016) and look at how this new information can be displayed. Notable extensions include: confidence, corpus frequency, orthographic variants, lexicalized and non-lexicalized synsets and lemmas, new parts of speech, and more. Many of these extensions already exist in multiple wordnets {--} the challenge was to find a compatible representation. To this end, we introduce a new version of the Open Multilingual Wordnet (Bond and Foster, 2013), that integrates a new set of tools that tests the extensions introduced by this new format, while also ensuring the integrity of the Collaborative Interlingual Index (CILI: Bond et al., 2016), avoiding the same new concept to be introduced through multiple projects.
Collocations in Russian Lexicography and Russian Collocations Database
Authors: Maria Khokhlova
Date: 2020-05-01 00:00:00
Proceeding: LREC 2020 5
Tasks: Clustering

The paper presents the issue of collocability and collocations in Russian and gives a survey of a wide range of dictionaries both printed and online ones that describe collocations. Our project deals with building a database that will include dictionary and statistical collocations. The former can be described in various lexicographic resources whereas the latter can be extracted automatically from corpora. Dictionaries differ among themselves, the information is given in various ways, making it hard for language learners and researchers to acquire data. A number of dictionaries were analyzed and processed to retrieve verified collocations, however the overlap between the lists of collocations extracted from them is still rather small. This fact indicates there is a need to create a unified resource which takes into account collocability and more examples. The proposed resource will also be useful for linguists and for studying Russian as a foreign language. The obtained results can be important for machine learning and for other NLP tasks, for instance, automatic clustering of word combinations and disambiguation.
Methodological Aspects of Developing and Managing an Etymological Lexical Resource: Introducing EtymDB-2.0
Authors: Cl{\'e}mentine Fourrier, Beno{\^\i}t Sagot
Date: 2020-05-01 00:00:00
Proceeding: LREC 2020 5
Tasks: Cognate Prediction, Machine Translation, Translation

Diachronic lexical information is not only important in the field of historical linguistics, but is also increasingly used in NLP, most recently for machine translation of low resource languages. Therefore, there is a need for fine-grained, large-coverage and accurate etymological lexical resources. In this paper, we propose a set of guidelines to generate such resources, for each step of the life-cycle of an etymological lexicon: creation, update, evaluation, dissemination, and exploitation. To illustrate the guidelines, we introduce EtymDB 2.0, an etymological database automatically generated from the Wiktionary, which contains 1.8 million lexemes, linked by more than 700,000 fine-grained etymological relations, across 2,536 living and dead languages. We also introduce use cases for which EtymDB 2.0 could represent a key resource, such as phylogenetic tree generation, low resource machine translation or medieval languages study.
OFrLex: A Computational Morphological and Syntactic Lexicon for Old French
Authors: Ga{\"e}l Guibon, Beno{\^\i}t Sagot
Date: 2020-05-01 00:00:00
Proceeding: LREC 2020 5
Tasks: Dependency Parsing, Part-Of-Speech Tagging

In this paper we describe our work on the development and enrichment of OFrLex, a freely available, large-coverage morphological and syntactic Old French lexicon. We rely on several heterogeneous language resources to extract structured and exploitable information. The extraction follows a semi-automatic procedure with substantial manual steps to respond to difficulties encountered while aligning lexical entries from distinct language resources. OFrLex aims at improving natural language processing tasks on Old French such as part-of-speech tagging and dependency parsing. We provide quantitative information on OFrLex and discuss its reliability. We also describe and evaluate a semi-automatic, word-embedding-based lexical enrichment process aimed at increasing the accuracy of the resource. Results of this extension technique will be manually validated in the near future, a step that will take advantage of OFrLex{'}s viewing, searching and editing interface, which is already accessible online.
Automatic Reconstruction of Missing Romanian Cognates and Unattested Latin Words
Authors: Alina Maria Ciobanu, Liviu P. Dinu, Laurentiu Zoicas
Date: 2020-05-01 00:00:00
Proceeding: LREC 2020 5
Tasks: Re-Ranking

Producing related words is a key concern in historical linguistics. Given an input word, the task is to automatically produce either its proto-word, a cognate pair or a modern word derived from it. In this paper, we apply a method for producing related words based on sequence labeling, aiming to fill in the gaps in incomplete cognate sets in Romance languages with Latin etymology (producing Romanian cognates that are missing) and to reconstruct uncertified Latin words. We further investigate an ensemble-based aggregation for combining and re-ranking the word productions of multiple languages.
A Multilingual Evaluation Dataset for Monolingual Word Sense Alignment
Authors: Sina Ahmadi, John Philip McCrae, Sanni Nimb, Fahad Khan, Monica Monachini, Bolette Pedersen, Thierry Declerck, Tanja Wissik, Bell, Andrea i, Irene Pisani, Thomas Troelsg{\aa}rd, Sussi Olsen, Simon Krek, Veronika Lipp, Tam{\'a}s V{\'a}radi, L{\'a}szl{\'o} Simon, Andr{\'a}s Gyorffy, Carole Tiberius, Tanneke Schoonheim, Yifat Ben Moshe, Maya Rudich, Raya Abu Ahmad, Dorielle Lonke, Kira Kovalenko, Margit Langemets, Jelena Kallas, Oksana Dereza, Theodorus Fransen, David Cillessen, David Lindemann, Mikel Alonso, Ana Salgado, Jos{\'e} Luis Sancho, Rafael-J. Ure{\~n}a-Ruiz, Jordi Porta Zamorano, Kiril Simov, Petya Osenova, Zara Kancheva, Ivaylo Radev, Ranka Stankovi{\'c}, Andrej Perdih, Dejan Gabrovsek
Date: 2020-05-01 00:00:00
Proceeding: LREC 2020 5

Aligning senses across resources and languages is a challenging task with beneficial applications in the field of natural language processing and electronic lexicography. In this paper, we describe our efforts in manually aligning monolingual dictionaries. The alignment is carried out at sense-level for various resources in 15 languages. Moreover, senses are annotated with possible semantic relationships such as broadness, narrowness, relatedness, and equivalence. In comparison to previous datasets for this task, this dataset covers a wide range of languages and resources and focuses on the more challenging task of linking general-purpose language. We believe that our data will pave the way for further advances in alignment and evaluation of word senses by creating new solutions, particularly those notoriously requiring data such as neural networks. Our resources are publicly available at https://github.com/elexis-eu/MWSA.
Computational Etymology and Word Emergence
Authors: Winston Wu, David Yarowsky
Date: 2020-05-01 00:00:00
Proceeding: LREC 2020 5

We developed an extensible, comprehensive Wiktionary parser that improves over several existing parsers. We predict the etymology of a word across the full range of etymology types and languages in Wiktionary, showing improvements over a strong baseline. We also model word emergence and show the application of etymology in modeling this phenomenon. We release our parser to further research in this understudied field.
A Dataset of Translational Equivalents Built on the Basis of plWordNet-Princeton WordNet Synset Mapping
Authors: Ewa Rudnicka, Tomasz Naskr{\k{e}}t
Date: 2020-05-01 00:00:00
Proceeding: LREC 2020 5
Tasks: Translation, Word Sense Disambiguation

The paper presents a dataset of 11,000 Polish-English translational equivalents in the form of pairs of plWordNet and Princeton WordNet lexical units linked by three types of equivalence links: strong equivalence, regular equivalence, and weak equivalence. The resource consists of the two subsets. The first subset was built in result of manual annotation of an extended sample of Polish-English sense pairs partly randomly extracted from synsets linked by interlingual relations such as I-synononymy, I-partial synonymy and I-hyponymy and partly manually selected from the surrounding synsets in the hypernymy hierarchy. The second subset was created as a result of the manual checkup of an automatically generated lists of pairs of sense equivalents on the basis of a couple of simple, rule-based heuristics. For both subsets, the same methodology of equivalence annotation was adopted based on the verification of a set of formal, semantic-pragmatic and translational features. The constructed dataset is a novum in the wordnet domain and can facilitate the precision of bilingual NLP tasks such as automatic translation, bilingual word sense disambiguation and sentiment annotation.
TRANSLIT: A Large-scale Name Transliteration Resource
Authors: Fern Benites, o, Gilbert Fran{\c{c}}ois Duivesteijn, Pius von D{\"a}niken, Mark Cieliebak
Date: 2020-05-01 00:00:00
Proceeding: LREC 2020 5
Tasks: Transliteration

Transliteration is the process of expressing a proper name from a source language in the characters of a target language (e.g. from Cyrillic to Latin characters). We present TRANSLIT, a large-scale corpus with approx. 1.6 million entries in more than 180 languages with about 3 million variations of person and geolocation names. The corpus is based on various public data sources, which have been transformed into a unified format to simplify their usage, plus a newly compiled dataset from Wikipedia. In addition, we apply several machine learning methods to establish baselines for automatically detecting transliterated names in various languages. Our best systems achieve an accuracy of 92{\%} on identification of transliterated pairs.
Computing with Subjectivity Lexicons
Authors: Caio L. M. Jeronimo, Claudio E. C. Campelo, Le Balby Marinho, ro, Allan Sales, Adriano Veloso, Roberta Viola
Date: 2020-05-01 00:00:00
Proceeding: LREC 2020 5
Tasks: Automated Essay Scoring, News Classification

In this paper, we introduce a new set of lexicons for expressing subjectivity in text documents written in Brazilian Portuguese. Besides the non-English idiom, in contrast to other subjectivity lexicons available, these lexicons represent different subjectivity dimensions (other than sentiment) and are more compact in number of terms. This last feature was designed intentionally to leverage the power of word embedding techniques, i.e., with the words mapped to an embedding space and the appropriate distance measures, we can easily capture semantically related words to the ones in the lexicons. Thus, we do not need to build comprehensive vocabularies and can focus on the most representative words for each lexicon dimension. We showcase the use of these lexicons in three highly non-trivial tasks: (1) Automated Essay Scoring in the Presence of Biased Ratings, (2) Subjectivity Bias in Brazilian Presidential Elections and (3) Fake News Classification Based on Text Subjectivity. All these tasks involve text documents written in Portuguese.
The ACoLi Dictionary Graph
Authors: Christian Chiarcos, Christian F{\"a}th, Maxim Ionov
Date: 2020-05-01 00:00:00
Proceeding: LREC 2020 5
Tasks: Translation

In this paper, we report the release of the ACoLi Dictionary Graph, a large-scale collection of multilingual open source dictionaries available in two machine-readable formats, a graph representation in RDF, using the OntoLex-Lemon vocabulary, and a simple tabular data format to facilitate their use in NLP tasks, such as translation inference across dictionaries. We describe the mapping and harmonization of the underlying data structures into a unified representation, its serialization in RDF and TSV, and the release of a massive and coherent amount of lexical data under open licenses.
Resources in Underrepresented Languages: Building a Representative Romanian Corpus
Authors: Ludmila Midrigan - Ciochina, Victoria Boyd, Lucila Sanchez-Ortega, Diana Malancea{\_}Malac, Doina Midrigan, David P. Corina
Date: 2020-05-01 00:00:00
Proceeding: LREC 2020 5

The effort in the field of Linguistics to develop theories that aim to explain language-dependent effects on language processing is greatly facilitated by the availability of reliable resources representing different languages. This project presents a detailed description of the process of creating a large and representative corpus in Romanian {--} a relatively under-resourced language with unique structural and typological characteristics, that can be used as a reliable language resource for linguistic studies. The decisions that have guided the construction of the corpus, including the type of corpus, its size and component resource files are discussed. Issues related to data collection, data organization and storage, as well as characteristics of the data included in the corpus are described. Currently, the corpus has approximately 5,500,000 tokens originating from written text and 100,000 tokens of spoken language. it includes language samples that represent a wide variety of registers (i.e. written language - 16 registers and 5 registers of spoken language), as well as different authors and speakers
World Class Language Technology - Developing a Language Technology Strategy for Danish
Authors: Sabine Kirchmeier, Bolette Pedersen, Sanni Nimb, Philip Diderichsen, Peter Juel Henrichsen
Date: 2020-05-01 00:00:00
Proceeding: LREC 2020 5

Although Denmark is one of the most digitized countries in Europe, no coordinated efforts have been made in recent years to support the Danish language with regard to language technology and artificial intelligence. In March 2019, however, the Danish government adopted a new, ambitious strategy for LT and artificial intelligence. In this paper, we describe the process behind the development of the language-related parts of the strategy: A Danish Language Technology Committee was constituted and a comprehensive series of workshops were organized in which users, suppliers, developers, and researchers gave their valuable input based on their experiences. We describe how, based on this experience, the focus areas and recommendations for the LT strategy were established, and which steps are currently taken in order to put the strategy into practice.
Corpora of Disordered Speech in the Light of the GDPR: Two Use Cases from the DELAD Initiative
Authors: Henk van den Heuvel, Aleksei Kelli, Katarzyna Klessa, Satu Salaasti
Date: 2020-05-01 00:00:00
Proceeding: LREC 2020 5

Corpora of disordered speech (CDS) are costly to collect and difficult to share due to personal data protection and intellectual property (IP) issues. In this contribution we discuss the legal grounds for processing CDS in the light of the GDPR, and illustrate these with two use cases from the DELAD context. One use case deals with clinical datasets and another with legacy data from Polish hearing-impaired children. For both cases, processing based on consent and on public interest are taken into consideration.