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= Natural Language Processing Seminar 2016–2017 = = Natural Language Processing Seminar 2018–2019 =
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||<style="border:0;padding-bottom:10px">The NLP Seminar is organised by the [[http://nlp.ipipan.waw.pl/|Linguistic Engineering Group]] at the [[http://www.ipipan.waw.pl/en/|Institute of Computer Science]], [[http://www.pan.pl/index.php?newlang=english|Polish Academy of Sciences]] (ICS PAS). It takes place on (some) Mondays, normally at 10:15 am, in the seminar room of the ICS PAS (ul. Jana Kazimierza 5, Warszawa). ||<style="border:0;padding-left:30px">[[seminarium|{{attachment:seminar-archive/pl.png}}]]|| ||<style="border:0;padding-bottom:10px">The NLP Seminar is organised by the [[http://nlp.ipipan.waw.pl/|Linguistic Engineering Group]] at the [[http://www.ipipan.waw.pl/en/|Institute of Computer Science]], [[http://www.pan.pl/index.php?newlang=english|Polish Academy of Sciences]] (ICS PAS). It takes place on (some) Mondays, normally at 10:15 am, in the seminar room of the ICS PAS (ul. Jana Kazimierza 5, Warszawa). All recorded talks are available [[https://www.youtube.com/channel/UC5PEPpMqjAr7Pgdvq0wRn0w|on YouTube]]. ||<style="border:0;padding-left:30px">[[seminarium|{{attachment:seminar-archive/pl.png}}]]||
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||<style="border:0;padding-top:5px;padding-bottom:5px">'''10 October 2016'''||
||<style="border:0;padding-left:30px;padding-bottom:0px">'''Katarzyna Pakulska''', '''Barbara Rychalska''', '''Krystyna Chodorowska''', '''Wojciech Walczak''', '''Piotr Andruszkiewicz''' (Samsung)||
||<style="border:0;padding-left:30px;padding-bottom:5px">'''[[attachment:seminarium-archiwum/2016-10-10.pdf|Paraphrase Detection Ensemble – SemEval 2016 winner]]''' &#160;{{attachment:seminarium-archiwum/icon-pl.gif|Talk delivered in Polish.}} {{attachment:seminarium-archiwum/icon-en.gif|Slides in English.}}||
||<style="border:0;padding-left:30px;padding-bottom:15px">This seminar describes the winning solution designed for a core track within the [[http://alt.qcri.org/semeval2016/task1/|SemEval 2016 English Semantic Textual Similarity]] task. The goal of the competition was to measure semantic similarity between two given sentences on a scale from 0 to 5. At the same time the solution should replicate human language understanding. The presented model is a novel hybrid of recursive auto-encoders from deep learning (RAE) and a !WordNet award-penalty system, enriched with a number of other similarity models and features used as input for Linear Support Vector Regression.||
||<style="border:0;padding-top:5px;padding-bottom:5px">'''1 October 2018'''||
||<style="border:0;padding-left:30px;padding-bottom:0px">'''Janusz S. Bień''' (University of Warsaw – prof. emeritus)||
||<style="border:0;padding-left:30px;padding-bottom:5px">[[https://www.youtube.com/watch?v=mOYzwpjTAf4|{{attachment:seminarium-archiwum/youtube.png}}]] '''[[attachment:seminarium-archiwum/2018-10-01.pdf|Electronic indexes to lexicographical resources]]''' &#160;{{attachment:seminarium-archiwum/icon-pl.gif|Talk delivered in Polish.}}||
||<style="border:0;padding-left:30px;padding-bottom:15px">We will focus on the indexes to lexicographical resources available online in !DjVu format. Such indexes can be browsed, searched, modified and created with the djview4poliqarp open source program; the origins and the history of the program will be briefly presented. Originally the index support was added to the program to handle the list of entries in the 19th century Linde's dictionary, but can be used conveniently also for other resources, as will be demonstrated on selected examples. In particular some new features, introduced to the program in the last months, will be presented publicly for the first time.||
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||<style="border:0;padding-top:5px;padding-bottom:5px">'''24 October 2016'''||
||<style="border:0;padding-left:30px;padding-bottom:0px">'''Adam Przepiórkowski, Jakub Kozakoszczak, Jan Winkowski, Daniel Ziembicki, Tadeusz Teleżyński''' (Institute of Computer Science, Polish Academy of Sciences / University of Warsaw)||
||<style="border:0;padding-left:30px;padding-bottom:5px">'''[[attachment:seminarium-archiwum/2016-10-24.pdf|Corpus of formalized textual entailment steps]]''' &#160;{{attachment:seminarium-archiwum/icon-pl.gif|Talk delivered in Polish.}}||
||<style="border:0;padding-left:30px;padding-bottom:15px">The authors present resources created within CLARIN project aiming to help with qualitative evaluation of RTE systems: two textual derivations corpora and a corpus of textual entailment rules. Textual derivation is a series of atomic steps which connects Text with Hypothesis in a textual entailment pair. Original pairs are taken from the FraCaS corpus and a polish translation of the RTE3 corpus. Textual entailment rule sanctions textual entailment relation between the input and the output of a step, using syntactic patterns written in the UD standard and some other semantic, logical and contextual constraints expressed in FOL.||
||<style="border:0;padding-top:5px;padding-bottom:5px">'''15 October 2018'''||
||<style="border:0;padding-left:30px;padding-bottom:0px">'''Wojciech Jaworski, Szymon Rutkowski''' (University of Warsaw)||
||<style="border:0;padding-left:30px;padding-bottom:5px">'''A multilayer rule based model of Polish inflection''' &#160;{{attachment:seminarium-archiwum/icon-pl.gif|Talk delivered in Polish.}}||
||<style="border:0;padding-left:30px;padding-bottom:15px">The presentation will be devoted to the multilayer model of Polish inflection. The model has been developed on the basis of Grammatical Dictionary of Polish; it does not use the concept of a inflexion paradigm. The model consists of three layers of hand-made rules: "orthographic-phonetic layer" converting a segment to representation reflecting morphological patterns of the language, "analytic layer" generating lemma and determining affix and "interpretation layer" giving a morphosyntactic interpretation based on detected affixes. The model provides knowledge about the language to a morphological analyzer supplemented with the function of guessing lemmas and morphosyntactic interpretations for non-dictionary forms (guesser). The second use of the model is generation of word forms based on lemma and morphosyntactic interpretation. The presentation will also cover the issue of disambiguation of the results provided by the morphological analyzer. The demo version of the program is available on the Internet.||
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||<style="border:0;padding-top:5px;padding-bottom:5px">'''7 November 2016'''||
||<style="border:0;padding-left:30px;padding-bottom:0px">'''Rafał Jaworski''' (Adam Mickiewicz University in Poznań)||
||<style="border:0;padding-left:30px;padding-bottom:5px">''' [[attachment:seminarium-archiwum/2016-11-07.pdf|Concordia – translation memory search algorithm]]''' &#160;{{attachment:seminarium-archiwum/icon-pl.gif|Talk delivered in Polish.}}||
||<style="border:0;padding-left:30px;padding-bottom:15px">The talk covers [[http://tmconcordia.sourceforge.net/|the Concordia algorithm]] which is used to maximize the productivity of a human translator. The algorithm combines the features of standard fuzzy translation memory searching with a concordancer. As the key non-functional requirement of computer-aided translation mechanisms is performance, Concordia incorporates upgraded versions of standard approximate searching techniques, aiming at reducing the computational complexity.||
||<style="border:0;padding-top:5px;padding-bottom:5px">'''29 October 2018'''||
||<style="border:0;padding-left:30px;padding-bottom:0px">'''Jakub Waszczuk''' (Heinrich-Heine-Universität Düsseldorf)||
||<style="border:0;padding-left:30px;padding-bottom:5px">'''Integrating multiword expression in syntactic parsing using A* and discriminative modeling methods''' &#160;{{attachment:seminarium-archiwum/icon-pl.gif|Talk delivered in Polish.}}||
||<style="border:0;padding-left:30px;padding-bottom:15px">During the seminar I will present two different approaches to identifying verbal multiword expressions (VMWEs) in coordination with syntactic parsing. The first approach consists in promoting MWEs in A* TAG (tree-adjoining grammar) parsing. It assumes that potential MWE candidates are pre-identified prior to parsing (e.g., as a result of MWE-aware supertagging). The experiments performed on Składnica showed that this strategy allows to significantly prune the parser's search space with little loss in syntactic parsing accuracy. In the second approach, VMWE identification is deferred to a post-processing phase in which (dependency) parsing results are already determined. VMWE identification is then reduced to the problem of dependency tree labeling, where one of two labels (MWE or not-MWE) must be predicted for each node in the dependency tree. A system based on this approach, using multiclass logistic regression for tree labeling, ranked 1st in the closed track of the PARSEME shared task 2018. A part of the talk will be also dedicated to Concraft-pl 2.0, the new version of a morphosyntactic tagger for Polish based on conditional random fields. Concraft-pl 2.0 performs morphosyntactic segmentation as a by-product of disambiguation, which allows to use it directly on the segmentation graphs provided by Morfeusz. This is in contrast with other existing taggers for Polish, which either neglect the problem of segmentation or rely on heuristics to perform it in a pre-processing stage.||
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||<style="border:0;padding-top:5px;padding-bottom:5px">'''21 November 2016'''||
||<style="border:0;padding-left:30px;padding-bottom:0px">'''Norbert Ryciak, Aleksander Wawer''' (Institute of Computer Science, Polish Academy of Sciences)||
||<style="border:0;padding-left:30px;padding-bottom:5px">[[https://www.youtube.com/watch?v=hGKzZxFa0ik|{{attachment:seminarium-archiwum/youtube.png}}]] '''[[attachment:seminarium-archiwum/2016-11-21.pdf|Using recursive deep neural networks and syntax to compute phrase semantics]]''' &#160;{{attachment:seminarium-archiwum/icon-pl.gif|Talk delivered in Polish.}}||
||<style="border:0;padding-left:30px;padding-bottom:15px">The seminar presents initial experiments on recursive phrase-level sentiment computation using dependency syntax and deep learning. We discuss neural network architectures and implementations created within Clarin 2 and present results on English language resources. Seminar also covers undergoing work on Polish language resources.||
||<style="border:0;padding-top:5px;padding-bottom:5px">'''5 November 2018'''||
||<style="border:0;padding-left:30px;padding-bottom:0px">'''Jakub Kozakoszczak''' (Faculty of Modern Languages, University of Warsaw / Heinrich-Heine-Universität Düsseldorf)||
||<style="border:0;padding-left:30px;padding-bottom:5px">'''Talk title will be available shortly''' &#160;{{attachment:seminarium-archiwum/icon-pl.gif|Talk delivered in Polish.}}||
||<style="border:0;padding-left:30px;padding-bottom:15px">Talk summary will be available shortly.||
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||<style="border:0;padding-top:5px;padding-bottom:5px">'''5 December 2017'''||
||<style="border:0;padding-left:30px;padding-bottom:0px">'''Dominika Rogozińska''', '''Marcin Woliński''' (Institute of Computer Science, Polish Academy of Sciences)||
||<style="border:0;padding-left:30px;padding-bottom:5px">'''[[attachment:seminarium-archiwum/2016-12-05.pdf|Methods of syntax disambiguation for constituent parse trees in Polish as post–processing phase of the Świgra parser]]''' &#160;{{attachment:seminarium-archiwum/icon-pl.gif|Talk delivered in Polish.}}||
||<style="border:0;padding-left:30px;padding-bottom:15px">The presentation shows methods of syntax disambiguation for Polish utterances produced by the Świgra parser. Presented methods include probabilistic context free grammars and maximum entropy models. The best of described models achieves efficiency measure at the level of 96.2%. The outcome of our experiments is a module for post-processing Świgra's parses.||
||<style="border:0;padding-top:5px;padding-bottom:5px">'''19 November 2018'''||
||<style="border:0;padding-left:30px;padding-bottom:0px">'''Daniel Zeman''' (Institute of Formal and Applied Linguistics, Charles University in Prague)||
||<style="border:0;padding-left:30px;padding-bottom:5px">'''Talk title will be available shortly''' &#160;{{attachment:seminarium-archiwum/icon-en.gif|Talk delivered in English.}}||
||<style="border:0;padding-left:30px;padding-bottom:15px">Talk summary will be available shortly.||
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||<style="border:0;padding-top:5px;padding-bottom:5px">'''9 January 2017'''||
||<style="border:0;padding-left:30px;padding-bottom:0px">'''Agnieszka Pluwak''' (Institute of Slavic Studies, Polish Academy of Sciences)||
||<style="border:0;padding-left:30px;padding-bottom:5px">''' [[attachment:seminarium-archiwum/2017-01-09.pdf|Building a domain-specific knowledge representation using an extended method of frame semantics on a corpus of Polish, English and German lease agreements]]''' &#160;{{attachment:seminarium-archiwum/icon-pl.gif|Wystąpienie w języku polskim.}}||
||<style="border:0;padding-left:30px;padding-bottom:15px">The !FrameNet project is defined by its authors as a lexical base with some ontological features (not an ontology sensu stricto, however, due to a selective approach towards description of frames and lexical units, as well as frame-to-frame relations). Ontologies, as knowledge representations in the field of NLP, should have the capacity of implementation to specific domains and texts, however, in the !FrameNet bibliography published before January 2016 I haven’t found a single knowledge representation based entirely on frames or on an extensive structure of frame-to-frame relations. I did find a few examples of domain-specific knowledge representations with the use of selected !FrameNet frames, such as !BioFrameNet or Legal !FrameNet, where frames were applied to connect data from different sources. Therefore, in my dissertation, I decided to conduct an experiment and build a knowledge representation of frame-to-frame relations for the domain of lease agreements. The aim of my study was the description of frames useful in case of building a possible data extraction system from lease agreements, this is frames containing answers to questions asked by a professional analyst while reading lease agreements. In my work I have asked several questions, e.g. would I be able to use !FrameNet frames for this purpose or would I have to build my own frames? Will the analysis of Polish cause language-specific problems? How will the professional language affect the use of frames in context? Etc.||
||<style="border:0;padding-top:5px;padding-bottom:5px">'''3 December 2018'''||
||<style="border:0;padding-left:30px;padding-bottom:0px">'''Ekaterina Lapshinova-Koltunski''' (Saarland University)||
||<style="border:0;padding-left:30px;padding-bottom:5px">'''Analysis and Annotation of Coreference for Contrastive Linguistics and Translation Studies''' &#160;{{attachment:seminarium-archiwum/icon-en.gif|Talk delivered in English.}}||
||<style="border:0;padding-left:30px;padding-bottom:15px">In this talk, I will report on the ongoing work on coreference analysis in a multilingual context. I will present two approaches in the analysis of coreference and coreference-related phenomena: (1) top-down or theory-driven: here we start from some linguistic knowledge derived from the existing frameworks, define linguistic categories to analyse and create an annotated corpus that can be used either for further linguistic analysis or as training data for NLP applications; (2) bottom-up or data-driven: in this case, we start from a set of features of shallow character that we believe are discourse-related. We extract these structures from a huge amount of data and analyse them from a linguistic point of view trying to describe and explain the observed phenomena from the point of view of existing theories and grammars.||
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||<style="border:0;padding-top:5px;padding-bottom:5px">'''23 January 2017'''||
||<style="border:0;padding-left:30px;padding-bottom:0px">'''Marek Rogalski''' (Lodz University of Technology)||
||<style="border:0;padding-left:30px;padding-bottom:5px">'''Automatic paraphrasing''' &#160;{{attachment:seminarium-archiwum/icon-pl.gif|Talk delivered in Polish.}}||
||<style="border:0;padding-left:30px;padding-bottom:15px">Paraphrasing is conveying the essential meaning of a message using different words. The ability to paraphrase is a measure of understanding. A teacher asking student a question "could you please tell us using your own words ...", tests whether the student has understood the topic. On this presentation we will discuss the task of automatic paraphrasing. We will differentiate between syntax-level paraphrases and essential-meaning-level paraphrases. We will bring up several techniques from seemingly unrelated fields that can be applied in automatic paraphrasing. We will also show results that we've been able to produce with those techniques.||

||<style="border:0;padding-top:5px;padding-bottom:5px">'''6 February 2017'''||
||<style="border:0;padding-left:30px;padding-bottom:0px">'''Łukasz Kobyliński''' (Institute of Computer Science, Polish Academy of Sciences)||
||<style="border:0;padding-left:30px;padding-bottom:5px">[[https://www.youtube.com/watch?v=TP9pmPKla1k|{{attachment:seminarium-archiwum/youtube.png}}]] '''[[attachment:seminarium-archiwum/2017-02-06.pdf|Korpusomat – a tool for creation of searcheable own corpora]]''' &#160;{{attachment:seminarium-archiwum/icon-pl.gif|Talk delivered in Polish.}}||
||<style="border:0;padding-left:30px;padding-bottom:15px">[[http://korpusomat.nlp.ipipan.waw.pl/|Korpusomat]] is a web tool facilitating unassisted creation of corpora for linguistic studies. After sending a set of text files they are automatically morphologically analysed and lemmatised using Morfeusz and disambiguated using Concraft tagger. The resulting corpus can be then downloaded and analysed offline using Poliqarp search engine to query for information related to text segmentation, base forms, inflectional interpretations and (dis)ambiguities. Poliqarp is also capable of calculating frequencies and applying basic statistical measures necessary for quantitative analysis. Apart from plain text files Korpusomat can also process more complex textual formats such as popular EPUBs, download source data from the Internet, strip unnecessary information and extract document metadata.||

||<style="border:0;padding-top:5px;padding-bottom:5px">'''20 February 2017''' (invited talk at [[https://ipipan.waw.pl/en/institute/scientific-activities/seminars/institute-seminar|the Institute seminar]])||
||<style="border:0;padding-left:30px;padding-bottom:0px">'''Elżbieta Hajnicz''' (Institute of Computer Science, Polish Academy of Sciences)||
||<style="border:0;padding-left:30px;padding-bottom:5px">[[https://youtu.be/lDKQ9jhIays|{{attachment:seminarium-archiwum/youtube.png}}]] '''[[https://ipipan.waw.pl/pliki/seminaria/20170220-Hajnicz.pdf|Representation language of the valency dictionary Walenty]]''' &#160;{{attachment:seminarium-archiwum/icon-pl.gif|The talk delivered in Polish.}}||
||<style="border:0;padding-left:30px;padding-bottom:15px">The Polish Valence Dictionary (Walenty) is intended to be used by natural language processing tools, particularly parsers, and thus it offers formalized representation of the valency information. The talk presented the notion of valency and its representation in the dictionary along with examples illustrating how particular syntactic and semantic language phenomena are modelled.||

||<style="border:0;padding-top:5px;padding-bottom:5px">'''2 March 2017'''||
||<style="border:0;padding-left:30px;padding-bottom:0px">'''Wojciech Jaworski''' (University of Warsaw)||
||<style="border:0;padding-left:30px;padding-bottom:5px">[[https://youtu.be/VgCsXsicoR8|{{attachment:seminarium-archiwum/youtube.png}}]] '''[[attachment:seminarium-archiwum/2017-03-02.pdf|Integration of dependency parser with a categorial parser]]''' &#160;{{attachment:seminarium-archiwum/icon-pl.gif|Talk delivered in Polish.}}||
||<style="border:0;padding-left:30px;padding-bottom:15px">As part of the talk I will describe the division of texts into sentences and controlling the execution of each parser within the emerging hybrid parser in the Clarin-bis project. I will describe the adopted method of dependency structure conversion aimed to make them compatible with the structures of categorial parser. The conversion will have two aspects: changing the attributes of each node and changing the links between nodes. I will depict how the method used can be extended to convert compressed forests generated by the parser Świgra. At the end I wil talk about the plans and the goals of reimplementation of the !MateParser algorithm.||

||<style="border:0;padding-top:5px;padding-bottom:5px">'''13 March 2017'''||
||<style="border:0;padding-left:30px;padding-bottom:0px">'''Marek Kozłowski, Szymon Roziewski''' (National Information Processing Institute)||
||<style="border:0;padding-left:30px;padding-bottom:5px">[[https://youtu.be/3mtjJfI3HkU|{{attachment:seminarium-archiwum/youtube.png}}]] '''[[attachment:seminarium-archiwum/2017-03-13.pdf|Internet model of Polish and semantic text processing]]''' &#160;{{attachment:seminarium-archiwum/icon-pl.gif|Talk delivered in Polish.}}||

||<style="border:0;padding-left:30px;padding-bottom:15px">The presentation shows how [[http://babelnet.org/|BabelNet]] (the multilingual encyclopaedia and semantic network based on publicly available data sources such as Wikipedia and !WordNet), can be used in the task of grouping short texts, sentiment analysis or emotional profiling of movies based on their subtitles. The second part presents the work based on [[http://commoncrawl.org/|CommonCrawl]] – publicly available petabyte-size open repository of multilingual Web pages. !CommonCrawl was used to build two models of Polish: n-gram-based and semantic distribution-based.||

||<style="border:0;padding-top:5px;padding-bottom:5px">'''20 March 2017'''||
||<style="border:0;padding-left:30px;padding-bottom:0px">'''Jakub Szymanik''' (University of Amsterdam)||
||<style="border:0;padding-left:30px;padding-bottom:5px">[[https://www.youtube.com/watch?v=OzftWhtGoAU|{{attachment:seminarium-archiwum/youtube.png}}]] '''[[attachment:seminarium-archiwum/2017-03-20.pdf|Exploring the Relation of Semantic Complexity and Quantifier Distribution in Large Corpora]]''' &#160;{{attachment:seminarium-archiwum/icon-pl.gif|Talk delivered in Polish.}} {{attachment:seminarium-archiwum/icon-en.gif|Slides in English.}}||
||<style="border:0;padding-left:30px;padding-bottom:15px">In this joint paper with Camilo Thorne, we study whether semantic complexity influences the distribution of generalized quantifiers in a large English corpus derived from Wikipedia. We consider the minimal computational device recognizing a generalized quantifier as the core measure of its semantic complexity. We regard quantifiers that belong to three increasingly more complex classes: Aristotelian (recognizable by 2-state acyclic finite automata), counting (k+2-state finite automata), and proportional quantifiers (pushdown automata). Using regression analysis we show that semantic complexity is a statistically significant factor explaining 27.29% of frequency variation. We compare this impact to that of other known sources of complexity, both semantic (quantifier monotonicity and the comparative/superlative distinction) and superficial (e.g., the length of quantifier surface forms). In general, we observe that the more complex a quantifier, the less frequent it is.||

||<style="border:0;padding-top:5px;padding-bottom:5px">'''27 March 2017''' (invited talk at [[https://ipipan.waw.pl/en/institute/scientific-activities/seminars/institute-seminar|the institute seminar]])||
||<style="border:0;padding-left:30px;padding-bottom:0px">'''Paweł Morawiecki''' (Institute of Computer Science, Polish Academy of Sciences)||
||<style="border:0;padding-left:30px;padding-bottom:5px">[[https://www.youtube.com/watch?v=onaYI6XY1S4|{{attachment:seminarium-archiwum/youtube.png}}]] '''[[attachment:seminarium-archiwum/2017-03-27.pdf|Introduction to deep neural networks]]''' &#160;{{attachment:seminarium-archiwum/icon-pl.gif|Talk delivered in Polish.}}||
||<style="border:0;padding-left:30px;padding-bottom:15px">In the last few years, Deep Neural Networks (DNN) has become a tool that provides the best solution for many problems from image and speech recognition. Also in natural language processing DNN totally revolutionizes the way how translation or word representation is done (and for many other problems). This presentation aims to provide good intuitions related to the DNN, their core architectures and how they operate. I will discuss and suggest the tools and source materials that can help in the further exploration of the topic and independent experiments.||

||<style="border:0;padding-top:5px;padding-bottom:5px">'''3 April 2017'''||
||<style="border:0;padding-left:30px;padding-bottom:0px">'''Katarzyna Budzynska''', '''Chris Reed''' (Institute of Philosophy and Sociology, Polish Academy of Sciences / University of Dundee)||
||<style="border:0;padding-left:30px;padding-bottom:5px">'''[[attachment:seminarium-archiwum/2017-04-03.pdf|Argument Corpora, Argument Mining and Argument Analytics (part I)]]''' &#160;{{attachment:seminarium-archiwum/icon-en.gif|Talk delivered in English.}}||
||<style="border:0;padding-left:30px;padding-bottom:15px">Argumentation, the most prominent way people communicate, has been attracting a lot of attention since the very beginning of the scientific reflection. [[http://www.arg.tech|The Centre for Argument Technology]] has been developing the infrastructure for studying argument structures for almost two decades. Our approach demonstrate several characteristics. First, we build upon the graph-based standard for argument representation, Argument Interchange Format AIF (Rahwan et al., 2007); and Inference Anchoring Theory IAT (Budzynska and Reed, 2011) which allows us to capture dialogic context of argumentation. Second, we focus on a variety of aspects of argument structures such as argumentation schemes (Lawrence and Reed, 2016); illocutionary intentions speakers associate with arguments (Budzynska et al., 2014a); ethos of arguments' authors (Duthie et al., 2016); rephrase relation which paraphrases parts of argument structures (Konat et al., 2016); and protocols of argumentative dialogue games (Yaskorska and Budzynska, forthcoming).||

||<style="border:0;padding-top:5px;padding-bottom:5px">'''10 April 2017'''||
||<style="border:0;padding-left:30px;padding-bottom:0px">'''Paweł Morawiecki''' (Institute of Computer Science, Polish Academy of Sciences)||
||<style="border:0;padding-left:30px;padding-bottom:5px">[[https://www.youtube.com/watch?v=6H9oUYsfaw8|{{attachment:seminarium-archiwum/youtube.png}}]] '''[[attachment:seminarium-archiwum/2017-04-10.pdf|Neural nets for natural language processing – selected architectures and problems]]''' &#160;{{attachment:seminarium-archiwum/icon-pl.gif|Talk delivered in Polish.}}||
||<style="border:0;padding-left:30px;padding-bottom:15px">For the last few years more and more problems in NLP have been successfully tackled with neural nets, particularly with deep architectures. These are such problems as sentiment analysis, topic classification, coreference, word representations and image labelling. In this talk i will give some details on most promising architectures used in NLP including recurrent and convolutional nets. The presented solutions will be given in a context of a concrete problem, namely the coreference problem in Polish language.||

||<style="border:0;padding-top:5px;padding-bottom:5px">'''15 May 2017'''||
||<style="border:0;padding-left:30px;padding-bottom:0px">'''Katarzyna Budzynska''', '''Chris Reed''' (Institute of Philosophy and Sociology, Polish Academy of Sciences / University of Dundee)||
||<style="border:0;padding-left:30px;padding-bottom:5px">'''[[attachment:seminarium-archiwum/2017-05-15.pdf|Argument Corpora, Argument Mining and Argument Analytics (part II)]]''' &#160;{{attachment:seminarium-archiwum/icon-en.gif|Talk delivered in English.}}||
||<style="border:0;padding-left:30px;padding-bottom:15px">In the second part of our presentation we will describe characteristics of argument structures using examples from our [[http://corpora.aifdb.org|AIF corpora of annotated argument structures]] in various domains and genres (see also [[http://ova.arg-tech.org|OVA+ annotation tool]]) including moral radio debates (Budzynska et al., 2014b); Hansard records of the UK parliamentary debates (Duthie et al., 2016); e-participation (Konat et al., 2016; Lawrence et al., forthcoming); and the US 2016 presidential debates (Visser et al., forthcoming). Finally, we will show how such complex argument structures, which on the one hand make the annotation process more time-consuming and less reliable, can on the other hand result in automatic extraction of a variety of valuable information when applying technologies for argument mining (Budzynska and Villata, 2017; Lawrence and Reed, forthcoming) and argument analytics (Reed et al., forthcoming).||

||<style="border:0;padding-top:5px;padding-bottom:5px">'''12 June 2017''' (invited talk at [[https://ipipan.waw.pl/en/institute/scientific-activities/seminars/institute-seminar|the Institute seminar]])||
||<style="border:0;padding-left:30px;padding-bottom:0px">'''Adam Pawłowski''' (University of Wroclaw)||
||<style="border:0;padding-left:30px;padding-bottom:5px">[[https://www.youtube.com/watch?v=RNIThH3b4uQ|{{attachment:seminarium-archiwum/youtube.png}}]] '''Sequential structures in texts''' &#160;{{attachment:seminarium-archiwum/icon-pl.gif|Talk delivered in Polish.}}||
||<style="border:0;padding-left:30px;padding-bottom:15px">The subject of my lecture is the phenomenon of sequentiality in linguistics. Sequentiality is defined here as a characteristic feature of a text or of a collection of texts, which expresses the sequential relationship between units of the same type, ordered along the axis of time or according to a different variable (e.g. the sequence of reading or publishing). In order to model sequentiality which is thus understood, we can use, among others, time series, spectral analysis, theory of stochastic processes, theory of information or some tools of acoustics.Referring to both my own research and existing literature, in my lecture I will be presenting sequential structures and selected models thereof in continuous texts, as well as models used in relation to sequences of several texts (known as chronologies of works); I will equally mention glottochronology, which is a branch of quantitative linguistics that aims at mathematical modeling of the development of language over long periods of time. Finally, I will relate to philosophical attempts to elucidate sequentiality (the notion of the text’s ‘memory’, the result chain, Pitagoreism, Platonism).||
||<style="border:0;padding-top:5px;padding-bottom:5px">'''7 January 2019'''||
||<style="border:0;padding-left:30px;padding-bottom:0px">'''Adam Przepiórkowski''' (Institute of Computer Science, Polish Academy of Sciences / University of Warsaw), '''Agnieszka Patejuk''' (Institute of Computer Science, Polish Academy of Sciences / University of Oxford)||
||<style="border:0;padding-left:30px;padding-bottom:5px">'''Talk title will be available shortly''' &#160;{{attachment:seminarium-archiwum/icon-pl.gif|Talk delivered in Polish.}}||
||<style="border:0;padding-left:30px;padding-bottom:15px">Talk summary will be available shortly.||
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||<style="border:0;padding-top:10px">Please see also [[http://nlp.ipipan.waw.pl/NLP-SEMINAR/previous-e.html|the talks given between 2000 and 2015]] and [[http://zil.ipipan.waw.pl/seminar-archive|2015–16]].|| ||<style="border:0;padding-top:10px">Please see also [[http://nlp.ipipan.waw.pl/NLP-SEMINAR/previous-e.html|the talks given in 2000–2015]] and [[http://zil.ipipan.waw.pl/seminar-archive|2015–2018]].||

Natural Language Processing Seminar 2018–2019

The NLP Seminar is organised by the Linguistic Engineering Group at the Institute of Computer Science, Polish Academy of Sciences (ICS PAS). It takes place on (some) Mondays, normally at 10:15 am, in the seminar room of the ICS PAS (ul. Jana Kazimierza 5, Warszawa). All recorded talks are available on YouTube.

seminarium

1 October 2018

Janusz S. Bień (University of Warsaw – prof. emeritus)

https://www.youtube.com/watch?v=mOYzwpjTAf4 Electronic indexes to lexicographical resources  Talk delivered in Polish.

We will focus on the indexes to lexicographical resources available online in DjVu format. Such indexes can be browsed, searched, modified and created with the djview4poliqarp open source program; the origins and the history of the program will be briefly presented. Originally the index support was added to the program to handle the list of entries in the 19th century Linde's dictionary, but can be used conveniently also for other resources, as will be demonstrated on selected examples. In particular some new features, introduced to the program in the last months, will be presented publicly for the first time.

15 October 2018

Wojciech Jaworski, Szymon Rutkowski (University of Warsaw)

A multilayer rule based model of Polish inflection  Talk delivered in Polish.

The presentation will be devoted to the multilayer model of Polish inflection. The model has been developed on the basis of Grammatical Dictionary of Polish; it does not use the concept of a inflexion paradigm. The model consists of three layers of hand-made rules: "orthographic-phonetic layer" converting a segment to representation reflecting morphological patterns of the language, "analytic layer" generating lemma and determining affix and "interpretation layer" giving a morphosyntactic interpretation based on detected affixes. The model provides knowledge about the language to a morphological analyzer supplemented with the function of guessing lemmas and morphosyntactic interpretations for non-dictionary forms (guesser). The second use of the model is generation of word forms based on lemma and morphosyntactic interpretation. The presentation will also cover the issue of disambiguation of the results provided by the morphological analyzer. The demo version of the program is available on the Internet.

29 October 2018

Jakub Waszczuk (Heinrich-Heine-Universität Düsseldorf)

Integrating multiword expression in syntactic parsing using A* and discriminative modeling methods  Talk delivered in Polish.

During the seminar I will present two different approaches to identifying verbal multiword expressions (VMWEs) in coordination with syntactic parsing. The first approach consists in promoting MWEs in A* TAG (tree-adjoining grammar) parsing. It assumes that potential MWE candidates are pre-identified prior to parsing (e.g., as a result of MWE-aware supertagging). The experiments performed on Składnica showed that this strategy allows to significantly prune the parser's search space with little loss in syntactic parsing accuracy. In the second approach, VMWE identification is deferred to a post-processing phase in which (dependency) parsing results are already determined. VMWE identification is then reduced to the problem of dependency tree labeling, where one of two labels (MWE or not-MWE) must be predicted for each node in the dependency tree. A system based on this approach, using multiclass logistic regression for tree labeling, ranked 1st in the closed track of the PARSEME shared task 2018. A part of the talk will be also dedicated to Concraft-pl 2.0, the new version of a morphosyntactic tagger for Polish based on conditional random fields. Concraft-pl 2.0 performs morphosyntactic segmentation as a by-product of disambiguation, which allows to use it directly on the segmentation graphs provided by Morfeusz. This is in contrast with other existing taggers for Polish, which either neglect the problem of segmentation or rely on heuristics to perform it in a pre-processing stage.

5 November 2018

Jakub Kozakoszczak (Faculty of Modern Languages, University of Warsaw / Heinrich-Heine-Universität Düsseldorf)

Talk title will be available shortly  Talk delivered in Polish.

Talk summary will be available shortly.

19 November 2018

Daniel Zeman (Institute of Formal and Applied Linguistics, Charles University in Prague)

Talk title will be available shortly  Talk delivered in English.

Talk summary will be available shortly.

3 December 2018

Ekaterina Lapshinova-Koltunski (Saarland University)

Analysis and Annotation of Coreference for Contrastive Linguistics and Translation Studies  Talk delivered in English.

In this talk, I will report on the ongoing work on coreference analysis in a multilingual context. I will present two approaches in the analysis of coreference and coreference-related phenomena: (1) top-down or theory-driven: here we start from some linguistic knowledge derived from the existing frameworks, define linguistic categories to analyse and create an annotated corpus that can be used either for further linguistic analysis or as training data for NLP applications; (2) bottom-up or data-driven: in this case, we start from a set of features of shallow character that we believe are discourse-related. We extract these structures from a huge amount of data and analyse them from a linguistic point of view trying to describe and explain the observed phenomena from the point of view of existing theories and grammars.

7 January 2019

Adam Przepiórkowski (Institute of Computer Science, Polish Academy of Sciences / University of Warsaw), Agnieszka Patejuk (Institute of Computer Science, Polish Academy of Sciences / University of Oxford)

Talk title will be available shortly  Talk delivered in Polish.

Talk summary will be available shortly.

Please see also the talks given in 2000–2015 and 2015–2018.