Towards new information resources for public health: From WordNet to MedicalWordNet

In the last two decades, WORDNET has evolved as the most comprehensive computational lexicon of general English. In this article, we discuss its potential for supporting the creation of an entirely new kind of information resource for public health, viz. MEDICAL WORDNET. This resource is not to be conceived merely as a lexical extension of the original WORDNET to medical terminology; indeed, there is already a considerable degree of overlap between WORDNET and the vocabulary of medicine. Instead, we propose a new type of repository, consisting of three large collections of (1) medically relevant word forms, structured along the lines of the existing Princeton WORDNET; (2) medically validated propositions, referred to here as medical facts, which will constitute what we shall call MEDICAL FACTNET; and (3) propositions reflecting laypersons’ medical beliefs, which will constitute what we shall call the MEDICAL BELIEFNET. We introduce a methodology for setting up the MEDICAL WORDNET. We then turn to the discussion of research challenges that have to be met in order to build this new type of information resource

Doctor of Philosophy

dissertationEvents are one important type of information throughout text. Event extraction is an information extraction (IE) task that involves identifying entities and objects (mainly noun phrases) that represent important roles in events of a particular type. However, the extraction performance of current event extraction systems is limited because they mainly consider local context (mostly isolated sentences) when making each extraction decision. My research aims to improve both coverage and accuracy of event extraction performance by explicitly identifying event contexts before extracting individual facts. First, I introduce new event extraction architectures that incorporate discourse information across a document to seek out and validate pieces of event descriptions within the document. TIER is a multilayered event extraction architecture that performs text analysis at multiple granularities to progressively \zoom in" on relevant event information. LINKER is a unied discourse-guided approach that includes a structured sentence classier to sequentially read a story and determine which sentences contain event information based on both the local and preceding contexts. Experimental results on two distinct event domains show that compared to previous event extraction systems, TIER can nd more event information while maintaining a good extraction accuracy, and LINKER can further improve extraction accuracy. Finding documents that describe a specic type of event is also highly challenging because of the wide variety and ambiguity of event expressions. In this dissertation, I present the multifaceted event recognition approach that uses event dening characteristics (facets), in addition to event expressions, to eectively resolve the complexity of event descriptions. I also present a novel bootstrapping algorithm to automatically learn event expressions as well as facets of events, which requires minimal human supervision. Experimental results show that the multifaceted event recognition approach can eectively identify documents that describe a particular type of event and make event extraction systems more precise

DravidianCodeMix: Sentiment Analysis and Offensive Language Identification Dataset for Dravidian Languages in Code-Mixed Text

This paper describes the development of a multilingual, manually annotated dataset for three under-resourced Dravidian languages generated from social media comments. The dataset was annotated for sentiment analysis and offensive language identification for a total of more than 60,000 YouTube comments. The dataset consists of around 44,000 comments in Tamil-English, around 7,000 comments in Kannada-English, and around 20,000 comments in Malayalam-English. The data was manually annotated by volunteer annotators and has a high inter-annotator agreement in Krippendorff's alpha. The dataset contains all types of code-mixing phenomena since it comprises user-generated content from a multilingual country. We also present baseline experiments to establish benchmarks on the dataset using machine learning methods. The dataset is available on Github (https://github.com/bharathichezhiyan/DravidianCodeMix-Dataset) and Zenodo (https://zenodo.org/record/4750858\#.YJtw0SYo\_0M).Comment: 36 page

Understanding complex constructions: a quantitative corpus-linguistic approach to the processing of english relative clauses

Die vorliegende Arbeit präsentiert einen korpusbasierten Ansatz an die kognitive Verarbeitung komplexer linguistische Konstruktionen am Beispiel englischer Relativsatzkonstruktionen (RCC). Im theoretischen Teil wird für eine konstruktionsgrammatische Perspektive auf sprachliches Wissen argumentiert, welche erlaubt, RCCs als schematische Konstruktionen zu charakterisieren. Diese Perspektive wird mit Konzeptionen exemplarbasierter Modelle menschlicher Sprachverarbeitung zusammengeführt, welche die Verarbeitung einer linguistischen Struktur als Funktion von der Häufigkeit vergangener Verarbeitungen typidentischer Vorkommnisse begreift. Häufige Strukturen gelangen demnach zu einem priviligierten Status im kognitiven System eines Sprechers, welcher in konstruktionsgrammatischen Theorien als entrenchment bezeichnet wird. Während der jeweilge entrenchment-Wert einer gegebenen Konstruktion für konkrete Zeichen vergleichsweise einfach zu bestimmen ist, wird die Einschätzung mit ansteigender Komplexität und Schematizität der Zielkonstruktion zunehmend schwieriger. Für höherstufige N-gramme, welche durch eine grosse Anzahl an variablen Positionen ausgezeichnet sind, ist das Feld noch vergleichweise unerforscht. Die vorliegende Arbeit ist bemüht, diese Lücke zu schließen entwickelt eine korpusbasierte mehrstufige Messprozedur, um den entrenchment-Wert komplexer schematischer Konstruktionen zu erfassen. Da linguistisches Wissen hochstrukturiert ist und menschliche Sprachverarbeitungsprozesse struktursensitiv sind, wird ein clusteranalytisches Verfahren angewendet, welches die salienten RCC hinsichtlich ihrer strukturellen Ähnlichlichkeit organisiert. Aus der Position einer RCC im konstruktionalen Netzwerk sowie dessen entrenchment-Wert kann nun der Grad der erwarteteten Verarbeitungsschwierigkeit abgeleitet werden. Der abschliessende Teil der Arbeit interpretiert die Ergebnisse vor dem Hintergrung psycholinguistischer Befunde zur Relativsatzverarbeitung

Sentiment Analysis: State of the Art

We present the state of art in sentiment analysis which covers the purpose of sentiment analysis, levels of sentiment analysis and processes that could be used to measure polarity and classify labels. Moreover, brief details about some resources of sentiment analysis are included

The use of and-coordination in terms of its syntactic (a)symmetry in argumentative essays : a corpus-based study of three university learner groups in MICUSP and NUCLE.

Studies found EL learners overuse and as an additive connector at the sentence-initial position (Bolton, Hung, & Nelson, 2002), and they underuse and as a coordinator (Leung, 2005). Generally, the use of the and-coordinator has often been overlooked in corpus research and in English teaching because of its seemingly simplicity. To test previous findings about the and-coordinator and to examine the influence of English proficiency on the use of and in academic writing, three learner corpora--MICUSP-NNS (advanced level), MICUSP-NS (advanced level), and NUCLE-NNS (upper-intermediate) were compared, with regard to the use of (a)symmetric structures of the and-coordination. Each corpus contains 31 argumentative essays written by 31 university students

Directional adposition use in English, Swedish and Finnish

Directional adpositions such as to the left of describe where a Figure is in relation to a Ground. English and Swedish directional adpositions refer to the location of a Figure in relation to a Ground, whether both are static or in motion. In contrast, the Finnish directional adpositions edellä (in front of) and jäljessä (behind) solely describe the location of a moving Figure in relation to a moving Ground (Nikanne, 2003). When using directional adpositions, a frame of reference must be assumed for interpreting the meaning of directional adpositions. For example, the meaning of to the left of in English can be based on a relative (speaker or listener based) reference frame or an intrinsic (object based) reference frame (Levinson, 1996). When a Figure and a Ground are both in motion, it is possible for a Figure to be described as being behind or in front of the Ground, even if neither have intrinsic features. As shown by Walker (in preparation), there are good reasons to assume that in the latter case a motion based reference frame is involved. This means that if Finnish speakers would use edellä (in front of) and jäljessä (behind) more frequently in situations where both the Figure and Ground are in motion, a difference in reference frame use between Finnish on one hand and English and Swedish on the other could be expected. We asked native English, Swedish and Finnish speakers’ to select adpositions from a language specific list to describe the location of a Figure relative to a Ground when both were shown to be moving on a computer screen. We were interested in any differences between Finnish, English and Swedish speakers. All languages showed a predominant use of directional spatial adpositions referring to the lexical concepts TO THE LEFT OF, TO THE RIGHT OF, ABOVE and BELOW. There were no differences between the languages in directional adpositions use or reference frame use, including reference frame use based on motion. We conclude that despite differences in the grammars of the languages involved, and potential differences in reference frame system use, the three languages investigated encode Figure location in relation to Ground location in a similar way when both are in motion. Levinson, S. C. (1996). Frames of reference and Molyneux’s question: Crosslingiuistic evidence. In P. Bloom, M.A. Peterson, L. Nadel & M.F. Garrett (Eds.) Language and Space (pp.109-170). Massachusetts: MIT Press. Nikanne, U. (2003). How Finnish postpositions see the axis system. In E. van der Zee & J. Slack (Eds.), Representing direction in language and space. Oxford, UK: Oxford University Press. Walker, C. (in preparation). Motion encoding in language, the use of spatial locatives in a motion context. Unpublished doctoral dissertation, University of Lincoln, Lincoln. United Kingdo