Readability assessment and automatic text simplification, the analysis of basque complex structures

301 p.(eus); 217 (eng)Tesi-lan honetan, euskarazko testuen konplexutasuna eta sinplifikazioa automatikoki aztertzeko lehen urratsak egin ditugu. Testuen konplexutasuna aztertzeko, testuen sinplifikazio automatikoa helburu duten beste hizkuntzetako lanetan eta euskarazko corpusetan egindako azterketa linguistikoan oinarritu gara. Azterketa horietatik testuak automatikoki sinplifikatzeko oinarri linguistikoak ezarri ditugu. Konplexutasuna automatikoki analizatzeko, ezaugarri linguistikoetan eta ikasketa automatikoko tekniketan oinarrituta ErreXail sistema sortu eta inplementatu dugu.Horretaz gain, testuak automatikoki sinplifikatuko dituen Euskarazko Testuen Sinplifikatzailea (EuTS) sistemaren arkitektura diseinatu dugu, sistemaren modulu bakoitzean egingo diren eragiketak definituz eta, kasu-azterketa bezala,informazio biografikoa duten egitura parentetikoak sinplifikatuko dituen Biografix tresna eleaniztuna inplementatuz.Amaitzeko, Euskarazko Testu Sinplifikatuen Corpusa (ETSC) corpusa osatu dugu. Corpus hau baliatu dugu gure sinplifikaziorako azterketetatik ateratako hurbilpena beste batzuekin erkatzeko. Konparazio horiek egiteko, etiketatze-eskema bat ere definitu dugu

Natural Language Processing and Language Technologies for the Basque Language

The presence of a language in the digital domain is crucial for its survival, as online communication and digital language resources have become the standard in the last decades and will gain more importance in the coming years. In order to develop advanced systems that are considered the basics for an efficient digital communication (e.g. machine translation systems, text-to-speech and speech-to-text converters and digital assistants), it is necessary to digitalise linguistic resources and create tools. In the case of Basque, scholars have studied the creation of digital linguistic resources and the tools that allow the development of those systems for the last forty years. In this paper, we present an overview of the natural language processing and language technology resources developed for Basque, their impact in the process of making Basque a “digital language” and the applications and challenges in multilingual communication. More precisely, we present the well-known products for Basque, the basic tools and the resources that are behind the products we use every day. Likewise, we would like that this survey serves as a guide for other minority languages that are making their way to digitalisation. Received: 05 April 2022 Accepted: 20 May 202

Linking named entities to Wikipedia

Natural language is fraught with problems of ambiguity, including name reference. A name in text can refer to multiple entities just as an entity can be known by different names. This thesis examines how a mention in text can be linked to an external knowledge base (KB), in our case, Wikipedia. The named entity linking (NEL) task requires systems to identify the KB entry, or Wikipedia article, that a mention refers to; or, if the KB does not contain the correct entry, return NIL. Entity linking systems can be complex and we present a framework for analysing their different components, which we use to analyse three seminal systems which are evaluated on a common dataset and we show the importance of precise search for linking. The Text Analysis Conference (TAC) is a major venue for NEL research. We report on our submissions to the entity linking shared task in 2010, 2011 and 2012. The information required to disambiguate entities is often found in the text, close to the mention. We explore apposition, a common way for authors to provide information about entities. We model syntactic and semantic restrictions with a joint model that achieves state-of-the-art apposition extraction performance. We generalise from apposition to examine local descriptions specified close to the mention. We add local description to our state-of-the-art linker by using patterns to extract the descriptions and matching against this restricted context. Not only does this make for a more precise match, we are also able to model failure to match. Local descriptions help disambiguate entities, further improving our state-of-the-art linker. The work in this thesis seeks to link textual entity mentions to knowledge bases. Linking is important for any task where external world knowledge is used and resolving ambiguity is fundamental to advancing research into these problems

Analisi della leggibilità dei consensi informati: un approccio linguistico-computazionale

In questa tesi è presentato un approccio linguistico-computazionale al problema della valutazione della leggibilità di consensi informati. È illustrata una metodologia di analisi della leggibilità di un corpus di consensi informati basata su strumenti di annotazione linguistica. È inoltre presentata una metodologia volta a porre le basi alla creazione di uno strumento per la valutazione della leggibilità valido per più lingue. Infine sono presentati i primi risultati di una metodologia di semplificazione di un consenso informato

Investigating the Selection of Example Sentences for Unknown Target Words in ICALL Reading Texts for L2 German

Institute for Communicating and Collaborative SystemsThis thesis considers possible criteria for the selection of example sentences for difficult or unknown words in reading texts for students of German as a Second Language (GSL). The examples are intended to be provided within the context of an Intelligent Computer-Aided Language Learning (ICALL) Vocabulary Learning System, where students can choose among several explanation options for difficult words. Some of these options (e.g. glosses) have received a good deal of attention in the ICALL/Second Language (L2) Acquisition literature; in contrast, literature on examples has been the near exclusive province of lexicographers. The selection of examples is explored from an educational, L2 teaching point of view: the thesis is intended as a first exploration of the question of what makes an example helpful to the L2 student from the perspective of L2 teachers. An important motivation for this work is that selecting examples from a dictionary or randomly from a corpus has several drawbacks: first, the number of available dictionary examples is limited; second, the examples fail to take into account the context in which the word was encountered; and third, the rationale and precise principles behind the selection of dictionary examples is usually less than clear. Central to this thesis is the hypothesis that a random selection of example sentences from a suitable corpus can be improved by a guided selection process that takes into account characteristics of helpful examples. This is investigated by an empirical study conducted with teachers of L2 German. The teacher data show that four dimensions are significant criteria amenable to analysis: (a) reduced syntactic complexity, (b) sentence similarity, provision of (c) significant co-occurrences and (d) semantically related words. Models based on these dimensions are developed using logistic regression analysis, and evaluated through two further empirical studies with teachers and students of L2 German. The results of the teacher evaluation are encouraging: for the teacher evaluation, they indicate that, for one of the models, the top-ranked selections perform on the same level as dictionary examples. In addition, the model provides a ranking of potential examples that roughly corresponds to that of experienced teachers of L2 German. The student evaluation confirms and notably improves on the teacher evaluation in that the best-performing model of the teacher evaluation significantly outperforms both random corpus selections and dictionary examples (when a penalty for missing entries is included)

Parsing and Evaluation. Improving Dependency Grammars Accuracy. Anàlisi Sintàctica Automàtica i Avaluació. Millora de qualitat per a Gramàtiques de Dependències

Because parsers are still limited in analysing specific ambiguous constructions, the research presented in this thesis mainly aims to contribute to the improvement of parsing performance when it has knowledge integrated in order to deal with ambiguous linguistic phenomena. More precisely, this thesis intends to provide empirical solutions to the disambiguation of prepositional phrase attachment and argument recognition in order to assist parsers in generating a more accurate syntactic analysis. The disambiguation of these two highly ambiguous linguistic phenomena by the integration of knowledge about the language necessarily relies on linguistic and statistical strategies for knowledge acquisition. The starting point of this research proposal is the development of a rule-based grammar for Spanish and for Catalan following the theoretical basis of Dependency Grammar (Tesnière, 1959; Mel’čuk, 1988) in order to carry out two experiments about the integration of automatically- acquired knowledge. In order to build two robust grammars that understand a sentence, the FreeLing pipeline (Padró et al., 2010) has been used as a framework. On the other hand, an eclectic repertoire of criteria about the nature of syntactic heads is proposed by reviewing the postulates of Generative Grammar (Chomsky, 1981; Bonet and Solà, 1986; Haegeman, 1991) and Dependency Grammar (Tesnière, 1959; Mel’čuk, 1988). Furthermore, a set of dependency relations is provided and mapped to Universal Dependencies (Mcdonald et al., 2013). Furthermore, an empirical evaluation method has been designed in order to carry out both a quantitative and a qualitative analysis. In particular, the dependency parsed trees generated by the grammars are compared to real linguistic data. The quantitative evaluation is based on the Spanish Tibidabo Treebank (Marimon et al., 2014), which is large enough to carry out a real analysis of the grammars performance and which has been annotated with the same formalism as the grammars, syntactic dependencies. Since the criteria between both resources are differ- ent, a process of harmonization has been applied developing a set of rules that automatically adapt the criteria of the corpus to the grammar criteria. With regard to qualitative evaluation, there are no available resources to evaluate Spanish and Catalan dependency grammars quali- tatively. For this reason, a test suite of syntactic phenomena about structure and word order has been built. In order to create a representative repertoire of the languages observed, descriptive grammars (Bosque and Demonte, 1999; Solà et al., 2002) and the SenSem Corpus (Vázquez and Fernández-Montraveta, 2015) have been used for capturing relevant structures and word order patterns, respectively. Thanks to these two tools, two experiments have been carried out in order to prove that knowl- edge integration improves the parsing accuracy. On the one hand, the automatic learning of lan- guage models has been explored by means of statistical methods in order to disambiguate PP- attachment. More precisely, a model has been learned with a supervised classifier using Weka (Witten and Frank, 2005). Furthermore, an unsupervised model based on word embeddings has been applied (Mikolov et al., 2013a,b). The results of the experiment show that the supervised method is limited in predicting solutions for unseen data, which is resolved by the unsupervised method since provides a solution for any case. However, the unsupervised method is limited if it Parsing and Evaluation Improving Dependency Grammars Accuracy only learns from lexical data. For this reason, training data needs to be enriched with the lexical value of the preposition, as well as semantic and syntactic features. In addition, the number of patterns used to learn language models has to be extended in order to have an impact on the grammars. On the other hand, another experiment is carried out in order to improve the argument recog- nition in the grammars by the acquisition of linguistic knowledge. In this experiment, knowledge is acquired automatically from the extraction of verb subcategorization frames from the SenSem Corpus (Vázquez and Fernández-Montraveta, 2015) which contains the verb predicate and its arguments annotated syntactically. As a result of the information extracted, subcategorization frames have been classified into subcategorization classes regarding the patterns observed in the corpus. The results of the subcategorization classes integration in the grammars prove that this information increases the accuracy of the argument recognition in the grammars. The results of the research of this thesis show that grammars’ rules on their own are not ex- pressive enough to resolve complex ambiguities. However, the integration of knowledge about these ambiguities in the grammars may be decisive in the disambiguation. On the one hand, sta- tistical knowledge about PP-attachment can improve the grammars accuracy, but syntactic and semantic information, and new patterns of PP-attachment need to be included in the language models in order to contribute to disambiguate this phenomenon. On the other hand, linguistic knowledge about verb subcategorization acquired from annotated linguistic resources show a positive influence positively on grammars’ accuracy.Aquesta tesi vol tractar les limitacions amb què es troben els analitzadors sintàctics automàtics actualment. Tot i els progressos que s’han fet en l’àrea del Processament del Llenguatge Nat- ural en els darrers anys, les tecnologies del llenguatge i, en particular, els analitzadors sintàc- tics automàtics no han pogut traspassar el llindar de certes ambiguïtats estructurals com ara l’agrupació del sintagma preposicional i el reconeixement d’arguments. És per aquest motiu que la recerca duta a terme en aquesta tesi té com a objectiu aportar millores signiflcatives de quali- tat a l’anàlisi sintàctica automàtica per mitjà de la integració de coneixement lingüístic i estadístic per desambiguar construccions sintàctiques ambigües. El punt de partida de la recerca ha estat el desenvolupament de d’una gramàtica en espanyol i una altra en català basades en regles que segueixen els postulats de la Gramàtica de Dependèn- dencies (Tesnière, 1959; Mel’čuk, 1988) per tal de dur a terme els experiments sobre l’adquisició de coneixement automàtic. Per tal de crear dues gramàtiques robustes que analitzin i entenguin l’oració en profunditat, ens hem basat en l’arquitectura de FreeLing (Padró et al., 2010), una lli- breria de Processament de Llenguatge Natural que proveeix una anàlisi lingüística automàtica de l’oració. Per una altra banda, s’ha elaborat una proposta eclèctica de criteris lingüístics per determinar la formació dels sintagmes i les clàusules a la gramàtica per mitjà de la revisió de les propostes teòriques de la Gramàtica Generativa (Chomsky, 1981; Bonet and Solà, 1986; Haege- man, 1991) i de la Gramàtica de Dependències (Tesnière, 1959; Mel’čuk, 1988). Aquesta proposta s’acompanya d’un llistat de les etiquetes de relació de dependència que fan servir les regles de les gramàtques. A més a més de l’elaboració d’aquest llistat, s’han establert les correspondències amb l’estàndard d’anotació de les Dependències Universals (Mcdonald et al., 2013). Alhora, s’ha dissenyat un sistema d’avaluació empíric que té en compte l’anàlisi quantitativa i qualitativa per tal de fer una valoració completa dels resultats dels experiments. Precisament, es tracta una tasca empírica pel fet que es comparen les anàlisis generades per les gramàtiques amb dades reals de la llengua. Per tal de dur a terme l’avaluació des d’una perspectiva quan- titativa, s’ha fet servir el corpus Tibidabo en espanyol (Marimon et al., 2014) disponible només en espanyol que és prou extens per construir una anàlisi real de les gramàtiques i que ha estat anotat amb el mateix formalisme que les gramàtiques. En concret, per tal com els criteris de les gramàtiques i del corpus no són coincidents, s’ha dut a terme un procés d’harmonització de cri- teris per mitjà d’unes regles creades manualment que adapten automàticament l’estructura i la relació de dependència del corpus al criteri de les gramàtiques. Pel que fa a l’avaluació qualitativa, pel fet que no hi ha recursos disponibles en espanyol i català, hem dissenyat un reprertori de test de fenòmens sintàctics estructurals i relacionats amb l’ordre de l’oració. Amb l’objectiu de crear un repertori representatiu de les llengües estudiades, s’han fet servir gramàtiques descriptives per fornir el repertori d’estructures sintàctiques (Bosque and Demonte, 1999; Solà et al., 2002) i el Corpus SenSem (Vázquez and Fernández-Montraveta, 2015) per capturar automàticament l’ordre oracional. Gràcies a aquestes dues eines, s’han pogut dur a terme dos experiments per provar que la integració de coneixement en l’anàlisi sintàctica automàtica en millora la qualitat. D’una banda, Parsing and Evaluation Improving Dependency Grammars Accuracy s’ha explorat l’aprenentatge de models de llenguatge per mitjà de models estadístics per tal de proposar solucions a l’agrupació del sintagma preposicional. Més concretament, s’ha desen- volupat un model de llenguatge per mitjà d’un classiflcador d’aprenentatge supervisat de Weka (Witten and Frank, 2005). A més a més, s’ha après un model de llenguatge per mitjà d’un mètode no supervisat basat en l’aproximació distribucional anomenat word embeddings (Mikolov et al., 2013a,b). Els resultats de l’experiment posen de manifest que el mètode supervisat té greus lim- itacions per fer donar una resposta en dades que no ha vist prèviament, cosa que és superada pel mètode no supervisat pel fet que és capaç de classiflcar qualsevol cas. De tota manera, el mètode no supervisat que s’ha estudiat és limitat si aprèn a partir de dades lèxiques. Per aquesta raó, és necessari que les dades utilitzades per entrenar el model continguin el valor de la preposi- ció, trets sintàctics i semàntics. A més a més, cal ampliar el número de patrons apresos per tal d’ampliar la cobertura dels models i tenir un impacte en els resultats de les gramàtiques. D’una altra banda, s’ha proposat una manera de millorar el reconeixement d’arguments a les gramàtiques per mitjà de l’adquisició de coneixement lingüístic. En aquest experiment, s’ha op- tat per extreure automàticament el coneixement en forma de classes de subcategorització verbal d’el Corpus SenSem (Vázquez and Fernández-Montraveta, 2015), que conté anotats sintàctica- ment el predicat verbal i els seus arguments. A partir de la informació extreta, s’ha classiflcat les diverses diàtesis verbals en classes de subcategorització verbal en funció dels patrons observats en el corpus. Els resultats de la integració de les classes de subcategorització a les gramàtiques mostren que aquesta informació determina positivament el reconeixement dels arguments. Els resultats de la recerca duta a terme en aquesta tesi doctoral posen de manifest que les regles de les gramàtiques no són prou expressives per elles mateixes per resoldre ambigüitats complexes del llenguatge. No obstant això, la integració de coneixement sobre aquestes am- bigüitats pot ser decisiu a l’hora de proposar una solució. D’una banda, el coneixement estadístic sobre l’agrupació del sintagma preposicional pot millorar la qualitat de les gramàtiques, però per aflrmar-ho cal incloure informació sintàctica i semàntica en els models d’aprenentatge automàtic i capturar més patrons per contribuir en la desambiguació de fenòmens complexos. D’una al- tra banda, el coneixement lingüístic sobre subcategorització verbal adquirit de recursos lingüís- tics anotats influeix decisivament en la qualitat de les gramàtiques per a l’anàlisi sintàctica au- tomàtica

Automation of summarization evaluation methods and their application to the summarization process

Summarization is the process of creating a more compact textual representation of a document or a collection of documents. In view of the vast increase in electronically available information sources in the last decade, filters such as automatically generated summaries are becoming ever more important to facilitate the efficient acquisition and use of required information. Different methods using natural language processing (NLP) techniques are being used to this end. One of the shallowest approaches is the clustering of available documents and the representation of the resulting clusters by one of the documents; an example of this approach is the Google News website. It is also possible to augment the clustering of documents with a summarization process, which would result in a more balanced representation of the information in the cluster, NewsBlaster being an example. However, while some systems are already available on the web, summarization is still considered a difficult problem in the NLP community. One of the major problems hampering the development of proficient summarization systems is the evaluation of the (true) quality of system-generated summaries. This is exemplified by the fact that the current state-of-the-art evaluation method to assess the information content of summaries, the Pyramid evaluation scheme, is a manual procedure. In this light, this thesis has three main objectives. 1. The development of a fully automated evaluation method. The proposed scheme is rooted in the ideas underlying the Pyramid evaluation scheme and makes use of deep syntactic information and lexical semantics. Its performance improves notably on previous automated evaluation methods. 2. The development of an automatic summarization system which draws on the conceptual idea of the Pyramid evaluation scheme and the techniques developed for the proposed evaluation system. The approach features the algorithm for determining the pyramid and bases importance on the number of occurrences of the variable-sized contributors of the pyramid as opposed to word-based methods exploited elsewhere. 3. The development of a text coherence component that can be used for obtaining the best ordering of the sentences in a summary

Cappadocian kinship

Cappadocian kinship systems are very interesting from a sociolinguistic and anthropological perspective because of the mixture of inherited Greek and borrowed Turkish kinship terms. Precisely because the number of Turkish kinship terms differs from one variety to another, it is necessary to talk about Cappadocian kinship systems in the plural rather than about the Cappadocian kinship system in the singular. Although reference will be made to other Cappadocian varieties, this paper will focus on the kinship systems of Mišotika and Aksenitika, the two Central Cappadocian dialects still spoken today in several communities in Greece. Particular attention will be given to the use of borrowed Turkish kinship terms, which sometimes seem to co-exist together with their inherited Greek counterparts, e.g. mána vs. néne ‘mother’, ailfó/aelfó vs. γardáš ‘brother’ etc. In the final part of the paper some kinship terms with obscure or hitherto unknown etymology will be discussed, e.g. káka ‘grandmother’, ižá ‘aunt’, lúva ‘uncle (father’s brother)’ etc