Anna Nedoluzhko


2023

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Findings of the Second Shared Task on Multilingual Coreference Resolution
Zdeněk Žabokrtský | Miloslav Konopik | Anna Nedoluzhko | Michal Novák | Maciej Ogrodniczuk | Martin Popel | Ondrej Prazak | Jakub Sido | Daniel Zeman
Proceedings of the CRAC 2023 Shared Task on Multilingual Coreference Resolution

This paper summarizes the second edition of the shared task on multilingual coreference resolution, held with the CRAC 2023 workshop. Just like last year, participants of the shared task were to create trainable systems that detect mentions and group them based on identity coreference; however, this year’s edition uses a slightly different primary evaluation score, and is also broader in terms of covered languages: version 1.1 of the multilingual collection of harmonized coreference resources CorefUD was used as the source of training and evaluation data this time, with 17 datasets for 12 languages. 7 systems competed in this shared task.

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Overview of the Second Shared Task on Automatic Minuting (AutoMin) at INLG 2023
Tirthankar Ghosal | Ondřej Bojar | Marie Hledíková | Tom Kocmi | Anna Nedoluzhko
Proceedings of the 16th International Natural Language Generation Conference: Generation Challenges

In this article, we report the findings of the second shared task on Automatic Minuting (AutoMin) held as a Generation Challenge at the 16th International Natural Language Generation (INLG) Conference 2023. The second Automatic Minuting shared task is a successor to the first AutoMin which took place in 2021. The primary objective of the AutoMin shared task is to garner participation of the speech and natural language processing and generation community to create automatic methods for generating minutes from multi-party meetings. Five teams from diverse backgrounds participated in the shared task this year. A lot has changed in the Generative AI landscape since the last AutoMin especially with the emergence and wide adoption of Large Language Models (LLMs) to different downstream tasks. Most of the contributions are based on some form of an LLM and we are also adding current outputs of GPT4 as a benchmark. Furthermore, we examine the applicability of GPT-4 for automatic scoring of minutes. Compared to the previous instance of AutoMin, we also add another domain, the minutes for EU Parliament sessions, and we experiment with a more fine-grained manual evaluation. More details on the event can be found at https://ufal.github.io/automin-2023/.

2022

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Proceedings of the Fifth Workshop on Computational Models of Reference, Anaphora and Coreference
Maciej Ogrodniczuk | Sameer Pradhan | Anna Nedoluzhko | Vincent Ng | Massimo Poesio
Proceedings of the Fifth Workshop on Computational Models of Reference, Anaphora and Coreference

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Findings of the Shared Task on Multilingual Coreference Resolution
Zdeněk Žabokrtský | Miloslav Konopík | Anna Nedoluzhko | Michal Novák | Maciej Ogrodniczuk | Martin Popel | Ondřej Pražák | Jakub Sido | Daniel Zeman | Yilun Zhu
Proceedings of the CRAC 2022 Shared Task on Multilingual Coreference Resolution

This paper presents an overview of the shared task on multilingual coreference resolution associated with the CRAC 2022 workshop. Shared task participants were supposed to develop trainable systems capable of identifying mentions and clustering them according to identity coreference. The public edition of CorefUD 1.0, which contains 13 datasets for 10 languages, was used as the source of training and evaluation data. The CoNLL score used in previous coreference-oriented shared tasks was used as the main evaluation metric. There were 8 coreference prediction systems submitted by 5 participating teams; in addition, there was a competitive Transformer-based baseline system provided by the organizers at the beginning of the shared task. The winner system outperformed the baseline by 12 percentage points (in terms of the CoNLL scores averaged across all datasets for individual languages).

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The Second Automatic Minuting (AutoMin) Challenge: Generating and Evaluating Minutes from Multi-Party Meetings
Tirthankar Ghosal | Marie Hledíková | Muskaan Singh | Anna Nedoluzhko | Ondřej Bojar
Proceedings of the 15th International Conference on Natural Language Generation: Generation Challenges

We would host the AutoMin generation chal- lenge at INLG 2023 as a follow-up of the first AutoMin shared task at Interspeech 2021. Our shared task primarily concerns the automated generation of meeting minutes from multi-party meeting transcripts. In our first venture, we ob- served the difficulty of the task and highlighted a number of open problems for the community to discuss, attempt, and solve. Hence, we invite the Natural Language Generation (NLG) com- munity to take part in the second iteration of AutoMin. Like the first, the second AutoMin will feature both English and Czech meetings and the core task of summarizing the manually- revised transcripts into bulleted minutes. A new challenge we are introducing this year is to devise efficient metrics for evaluating the quality of minutes. We will also host an optional track to generate minutes for European parliamentary sessions. We carefully curated the datasets for the above tasks. Our ELITR Minuting Corpus has been recently accepted to LREC 2022 and publicly released. We are already preparing a new test set for evaluating the new shared tasks. We hope to carry forward the learning from the first AutoMin and instigate more community attention and interest in this timely yet chal- lenging problem. INLG, the premier forum for the NLG community, would be an appropriate venue to discuss the challenges and future of Automatic Minuting. The main objective of the AutoMin GenChal at INLG 2023 would be to come up with efficient methods to auto- matically generate meeting minutes and design evaluation metrics to measure the quality of the minutes.

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ALIGNMEET: A Comprehensive Tool for Meeting Annotation, Alignment, and Evaluation
Peter Polák | Muskaan Singh | Anna Nedoluzhko | Ondřej Bojar
Proceedings of the Thirteenth Language Resources and Evaluation Conference

Summarization is a challenging problem, and even more challenging is to manually create, correct, and evaluate the summaries. The severity of the problem grows when the inputs are multi-party dialogues in a meeting setup. To facilitate the research in this area, we present ALIGNMEET, a comprehensive tool for meeting annotation, alignment, and evaluation. The tool aims to provide an efficient and clear interface for fast annotation while mitigating the risk of introducing errors. Moreover, we add an evaluation mode that enables a comprehensive quality evaluation of meeting minutes. To the best of our knowledge, there is no such tool available. We release the tool as open source. It is also directly installable from PyPI.

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Constructing a Lexical Resource of Russian Derivational Morphology
Lukáš Kyjánek | Olga Lyashevskaya | Anna Nedoluzhko | Daniil Vodolazsky | Zdeněk Žabokrtský
Proceedings of the Thirteenth Language Resources and Evaluation Conference

Words of any language are to some extent related thought the ways they are formed. For instance, the verb ‘exempl-ify’ and the noun ‘example-s’ are both based on the word ‘example’, but the verb is derived from it, while the noun is inflected. In Natural Language Processing of Russian, the inflection is satisfactorily processed; however, there are only a few machine-trackable resources that capture derivations even though Russian has both of these morphological processes very rich. Therefore, we devote this paper to improving one of the methods of constructing such resources and to the application of the method to a Russian lexicon, which results in the creation of the largest lexical resource of Russian derivational relations. The resulting database dubbed DeriNet.RU includes more than 300 thousand lexemes connected with more than 164 thousand binary derivational relations. To create such data, we combined the existing machine-learning methods that we improved to manage this goal. The whole approach is evaluated on our newly created data set of manual, parallel annotation. The resulting DeriNet.RU is freely available under an open license agreement.

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ELITR Minuting Corpus: A Novel Dataset for Automatic Minuting from Multi-Party Meetings in English and Czech
Anna Nedoluzhko | Muskaan Singh | Marie Hledíková | Tirthankar Ghosal | Ondřej Bojar
Proceedings of the Thirteenth Language Resources and Evaluation Conference

Taking minutes is an essential component of every meeting, although the goals, style, and procedure of this activity (“minuting” for short) can vary. Minuting is a rather unstructured writing activity and is affected by who is taking the minutes and for whom the intended minutes are. With the rise of online meetings, automatic minuting would be an important benefit for the meeting participants as well as for those who might have missed the meeting. However, automatically generating meeting minutes is a challenging problem due to a variety of factors including the quality of automatic speech recorders (ASRs), availability of public meeting data, subjective knowledge of the minuter, etc. In this work, we present the first of its kind dataset on Automatic Minuting. We develop a dataset of English and Czech technical project meetings which consists of transcripts generated from ASRs, manually corrected, and minuted by several annotators. Our dataset, AutoMin, consists of 113 (English) and 53 (Czech) meetings, covering more than 160 hours of meeting content. Upon acceptance, we will publicly release (aaa.bbb.ccc) the dataset as a set of meeting transcripts and minutes, excluding the recordings for privacy reasons. A unique feature of our dataset is that most meetings are equipped with more than one minute, each created independently. Our corpus thus allows studying differences in what people find important while taking the minutes. We also provide baseline experiments for the community to explore this novel problem further. To the best of our knowledge AutoMin is probably the first resource on minuting in English and also in a language other than English (Czech).

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CorefUD 1.0: Coreference Meets Universal Dependencies
Anna Nedoluzhko | Michal Novák | Martin Popel | Zdeněk Žabokrtský | Amir Zeldes | Daniel Zeman
Proceedings of the Thirteenth Language Resources and Evaluation Conference

Recent advances in standardization for annotated language resources have led to successful large scale efforts, such as the Universal Dependencies (UD) project for multilingual syntactically annotated data. By comparison, the important task of coreference resolution, which clusters multiple mentions of entities in a text, has yet to be standardized in terms of data formats or annotation guidelines. In this paper we present CorefUD, a multilingual collection of corpora and a standardized format for coreference resolution, compatible with morphosyntactic annotations in the UD framework and including facilities for related tasks such as named entity recognition, which forms a first step in the direction of convergence for coreference resolution across languages.

2021

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Do UD Trees Match Mention Spans in Coreference Annotations?
Martin Popel | Zdeněk Žabokrtský | Anna Nedoluzhko | Michal Novák | Daniel Zeman
Findings of the Association for Computational Linguistics: EMNLP 2021

One can find dozens of data resources for various languages in which coreference - a relation between two or more expressions that refer to the same real-world entity - is manually annotated. One could also assume that such expressions usually constitute syntactically meaningful units; however, mention spans have been annotated simply by delimiting token intervals in most coreference projects, i.e., independently of any syntactic representation. We argue that it could be advantageous to make syntactic and coreference annotations convergent in the long term. We present a pilot empirical study focused on matches and mismatches between hand-annotated linear mention spans and automatically parsed syntactic trees that follow Universal Dependencies conventions. The study covers 9 datasets for 8 different languages.

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Is one head enough? Mention heads in coreference annotations compared with UD-style heads
Anna Nedoluzhko | Michal Novák | Martin Popel | Zdeněk Žabokrtský | Daniel Zeman
Proceedings of the Sixth International Conference on Dependency Linguistics (Depling, SyntaxFest 2021)

2018

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PAWS: A Multi-lingual Parallel Treebank with Anaphoric Relations
Anna Nedoluzhko | Michal Novák | Maciej Ogrodniczuk
Proceedings of the First Workshop on Computational Models of Reference, Anaphora and Coreference

We present PAWS, a multi-lingual parallel treebank with coreference annotation. It consists of English texts from the Wall Street Journal translated into Czech, Russian and Polish. In addition, the texts are syntactically parsed and word-aligned. PAWS is based on PCEDT 2.0 and continues the tradition of multilingual treebanks with coreference annotation. The paper focuses on the coreference annotation in PAWS and its language-specific differences. PAWS offers linguistic material that can be further leveraged in cross-lingual studies, especially on coreference.

2017

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Projection-based Coreference Resolution Using Deep Syntax
Michal Novák | Anna Nedoluzhko | Zdeněk Žabokrtský
Proceedings of the 2nd Workshop on Coreference Resolution Beyond OntoNotes (CORBON 2017)

The paper describes the system for coreference resolution in German and Russian, trained exclusively on coreference relations project ed through a parallel corpus from English. The resolver operates on the level of deep syntax and makes use of multiple specialized models. It achieves 32 and 22 points in terms of CoNLL score for Russian and German, respectively. Analysis of the evaluation results show that the resolver for Russian is able to preserve 66% of the English resolver’s quality in terms of CoNLL score. The system was submitted to the Closed track of the CORBON 2017 Shared task.

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CoNLL 2017 Shared Task: Multilingual Parsing from Raw Text to Universal Dependencies
Daniel Zeman | Martin Popel | Milan Straka | Jan Hajič | Joakim Nivre | Filip Ginter | Juhani Luotolahti | Sampo Pyysalo | Slav Petrov | Martin Potthast | Francis Tyers | Elena Badmaeva | Memduh Gokirmak | Anna Nedoluzhko | Silvie Cinková | Jan Hajič jr. | Jaroslava Hlaváčová | Václava Kettnerová | Zdeňka Urešová | Jenna Kanerva | Stina Ojala | Anna Missilä | Christopher D. Manning | Sebastian Schuster | Siva Reddy | Dima Taji | Nizar Habash | Herman Leung | Marie-Catherine de Marneffe | Manuela Sanguinetti | Maria Simi | Hiroshi Kanayama | Valeria de Paiva | Kira Droganova | Héctor Martínez Alonso | Çağrı Çöltekin | Umut Sulubacak | Hans Uszkoreit | Vivien Macketanz | Aljoscha Burchardt | Kim Harris | Katrin Marheinecke | Georg Rehm | Tolga Kayadelen | Mohammed Attia | Ali Elkahky | Zhuoran Yu | Emily Pitler | Saran Lertpradit | Michael Mandl | Jesse Kirchner | Hector Fernandez Alcalde | Jana Strnadová | Esha Banerjee | Ruli Manurung | Antonio Stella | Atsuko Shimada | Sookyoung Kwak | Gustavo Mendonça | Tatiana Lando | Rattima Nitisaroj | Josie Li
Proceedings of the CoNLL 2017 Shared Task: Multilingual Parsing from Raw Text to Universal Dependencies

The Conference on Computational Natural Language Learning (CoNLL) features a shared task, in which participants train and test their learning systems on the same data sets. In 2017, the task was devoted to learning dependency parsers for a large number of languages, in a real-world setting without any gold-standard annotation on input. All test sets followed a unified annotation scheme, namely that of Universal Dependencies. In this paper, we define the task and evaluation methodology, describe how the data sets were prepared, report and analyze the main results, and provide a brief categorization of the different approaches of the participating systems.

2016

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Abstract Coreference in a Multilingual Perspective: a View on Czech and German
Anna Nedoluzhko | Ekaterina Lapshinova-Koltunski
Proceedings of the Workshop on Coreference Resolution Beyond OntoNotes (CORBON 2016)

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Bridging Corpus for Russian in comparison with Czech
Anna Roitberg | Anna Nedoluzhko
Proceedings of the Workshop on Coreference Resolution Beyond OntoNotes (CORBON 2016)

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A new look at possessive reflexivization: A comparative study between Czech and Russian
Anna Nedoluzhko
Proceedings of the Workshop on Grammar and Lexicon: interactions and interfaces (GramLex)

The paper presents a contrastive description of reflexive possessive pronouns “svůj” in Czech and “svoj” in Russian. The research concerns syntactic, semantic and pragmatic aspects. With our analysis, we shed a new light on the already investigated issue, which comes from a detailed comparison of the phenomenon of possessive reflexivization in two typologically and genetically similar languages. We show that whereas in Czech, the possessive reflexivization is mostly limited to syntactic functions and does not go beyond the grammar, in Russian it gets additional semantic meanings and moves substan-tially towards the lexicon. The obtained knowledge allows us to explain heretofore unclear marginal uses of reflexives in each language.

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Coreference in Prague Czech-English Dependency Treebank
Anna Nedoluzhko | Michal Novák | Silvie Cinková | Marie Mikulová | Jiří Mírovský
Proceedings of the Tenth International Conference on Language Resources and Evaluation (LREC'16)

We present coreference annotation on parallel Czech-English texts of the Prague Czech-English Dependency Treebank (PCEDT). The paper describes innovations made to PCEDT 2.0 concerning coreference, as well as coreference information already present there. We characterize the coreference annotation scheme, give the statistics and compare our annotation with the coreference annotation in Ontonotes and Prague Dependency Treebank for Czech. We also present the experiments made using this corpus to improve the alignment of coreferential expressions, which helps us to collect better statistics of correspondences between types of coreferential relations in Czech and English. The corpus released as PCEDT 2.0 Coref is publicly available.

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From Interoperable Annotations towards Interoperable Resources: A Multilingual Approach to the Analysis of Discourse
Ekaterina Lapshinova-Koltunski | Kerstin Anna Kunz | Anna Nedoluzhko
Proceedings of the Tenth International Conference on Language Resources and Evaluation (LREC'16)

In the present paper, we analyse variation of discourse phenomena in two typologically different languages, i.e. in German and Czech. The novelty of our approach lies in the nature of the resources we are using. Advantage is taken of existing resources, which are, however, annotated on the basis of two different frameworks. We use an interoperable scheme unifying discourse phenomena in both frameworks into more abstract categories and considering only those phenomena that have a direct match in German and Czech. The discourse properties we focus on are relations of identity, semantic similarity, ellipsis and discourse relations. Our study shows that the application of interoperable schemes allows an exploitation of discourse-related phenomena analysed in different projects and on the basis of different frameworks. As corpus compilation and annotation is a time-consuming task, positive results of this experiment open up new paths for contrastive linguistics, translation studies and NLP, including machine translation.

2015

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Across Languages and Genres: Creating a Universal Annotation Scheme for Textual Relations
Ekaterina Lapshinova-Koltunski | Anna Nedoluzhko | Kerstin Anna Kunz
Proceedings of the 9th Linguistic Annotation Workshop

2013

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Generic noun phrases and annotation of coreference and bridging relations in the Prague Dependency Treebank
Anna Nedoluzhko
Proceedings of the 7th Linguistic Annotation Workshop and Interoperability with Discourse

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Translation of “It” in a Deep Syntax Framework
Michal Novák | Anna Nedoluzhko | Zdeněk Žabokrtský
Proceedings of the Workshop on Discourse in Machine Translation

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Annotators’ Certainty and Disagreements in Coreference and Bridging Annotation in Prague Dependency Treebank
Anna Nedoluzhko | Jiří Mírovský
Proceedings of the Second International Conference on Dependency Linguistics (DepLing 2013)

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How Dependency Trees and Tectogrammatics Help Annotating Coreference and Bridging Relations in Prague Dependency Treebank
Anna Nedoluzhko | Jiří Mírovský
Proceedings of the Second International Conference on Dependency Linguistics (DepLing 2013)

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Introducing the Prague Discourse Treebank 1.0
Lucie Poláková | Jiří Mírovský | Anna Nedoluzhko | Pavlína Jínová | Šárka Zikánová | Eva Hajičová
Proceedings of the Sixth International Joint Conference on Natural Language Processing

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Two Case Studies on Translating Pronouns in a Deep Syntax Framework
Michal Novák | Zdeněk Žabokrtský | Anna Nedoluzhko
Proceedings of the Sixth International Joint Conference on Natural Language Processing

2010

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Annotation Tool for Extended Textual Coreference and Bridging Anaphora
Jiří Mírovský | Petr Pajas | Anna Nedoluzhko
Proceedings of the Seventh International Conference on Language Resources and Evaluation (LREC'10)

We present an annotation tool for the extended textual coreference and the bridging anaphora in the Prague Dependency Treebank 2.0 (PDT 2.0). After we very briefly describe the annotation scheme, we focus on details of the annotation process from the technical point of view. We present the way of helping the annotators by several useful features implemented in the annotation tool, such as a possibility to combine surface and deep syntactic representation of sentences during the annotation, an automatic maintaining of the coreferential chain, underlining candidates for antecedents, etc. For studying differences among parallel annotations, the tool offers a simultaneous depicting of several annotations of the same data. The annotation tool can be used for other corpora too, as long as they have been transformed to the PML format. We present modifications of the tool for working with the coreference relations on other layers of language description, namely on the analytical layer and the morphological layer of PDT.

2009

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The Coding Scheme for Annotating Extended Nominal Coreference and Bridging Anaphora in the Prague Dependency Treebank
Anna Nedoluzhko | Jiří Mírovský | Petr Pajas
Proceedings of the Third Linguistic Annotation Workshop (LAW III)

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