Extracting Scales of Measurement Automatically from Biomedical Text with Special Emphasis on Comparative and Superlative Scales

Abstract In this thesis, the focus is on the topic of “Extracting Scales of Measurement Automatically from Biomedical Text with Special Emphasis on Comparative and Superlative Scales.” Comparison sentences, when considered as a critical part of scales of measurement, play a highly significant role in the process of gathering information from a large number of biomedical research papers. A comparison sentence is defined as any sentence that contains two or more entities that are being compared. This thesis discusses several different types of comparison sentences such as gradable comparisons and non-gradable comparisons. The main goal is extracting comparison sentences automatically from the full text of biomedical articles. Therefore, the thesis presents a Java program that could be used to analyze biomedical text to identify comparison sentences by matching the sentences in the text to 37 syntactic and semantic features. These features or qualities would be helpful to extract comparative sentences from any biomedical text. Two machine learning techniques are used with the 37 roles to assess the curated dataset. The results of this study are compared with earlier studies

Learning morphology with Morfette

Morfette is a modular, data-driven, probabilistic system which learns to perform joint morphological tagging and lemmatization from morphologically annotated corpora. The system is composed of two learning modules which are trained to predict morphological tags and lemmas using the Maximum Entropy classifier. The third module dynamically combines the predictions of the Maximum-Entropy models and outputs a probability distribution over tag-lemma pair sequences. The lemmatization module exploits the idea of recasting lemmatization as a classification task by using class labels which encode mappings from wordforms to lemmas. Experimental evaluation results and error analysis on three morphologically rich languages show that the system achieves high accuracy with no language-specific feature engineering or additional resources

Grammar practice : theory and practice

Fil: Luque Colombres, María Candelaria. Universidad Nacional de Córdoba. Facultad de Lenguas; Argentina.Fil: Meehan, Patricia. Universidad Nacional de Córdoba. Facultad de Lenguas; Argentina.Fil: Oliva, María Belén. Universidad Nacional de Córdoba. Facultad de Lenguas; Argentina.Fil: Rius, Natalia. Universidad Nacional de Córdoba. Facultad de Lenguas; Argentina.Fil: de Maussion, Ana. Universidad Nacional de Córdoba. Facultad de Lenguas; Argentina.Fil: Neyra, Vanina Pamela. Universidad Nacional de Córdoba. Facultad de Lenguas; Argentina.Our main objective when writing this handbook has been to design some kind of material that would provide the first-year university student at Facultad de Lenguas with the basic foundations of English grammar. Although this handout could be used as a self-study grammar guide, the student should bear in mind it is meant to be used as a complement of class work. Therefore, the material included in the present publication has not been organized according to the level of difficulty, but rather in accordance with the syllabus of the subject. Each chapter brings along graded exercises which have been carefully designed to improve and consolidate the grammar topics included in the syllabus of the subject. Finally, we would like to point out that to round off each unit, we have decided to include texts (often authentic ones) in an attempt to offer the student a new perspective on the subject: one which relates grammatical structure systematically to meaning and use.Fil: Luque Colombres, María Candelaria. Universidad Nacional de Córdoba. Facultad de Lenguas; Argentina.Fil: Meehan, Patricia. Universidad Nacional de Córdoba. Facultad de Lenguas; Argentina.Fil: Oliva, María Belén. Universidad Nacional de Córdoba. Facultad de Lenguas; Argentina.Fil: Rius, Natalia. Universidad Nacional de Córdoba. Facultad de Lenguas; Argentina.Fil: de Maussion, Ana. Universidad Nacional de Córdoba. Facultad de Lenguas; Argentina.Fil: Neyra, Vanina Pamela. Universidad Nacional de Córdoba. Facultad de Lenguas; Argentina

Organisation and Contents of Korean Pedagogical Grammar - With focus on Korean: A Comprehensive Grammar (Yeon & Brown)

This paper aims to discuss how Korean pedagogical grammar should be written in terms of organisation and description of content. The arguments in this paper will be presented in practical and empirical manners rather than theoretical ones. The problematic questions and empirical issues presented arose while the author was writing a pedagogical grammar book entitled ‘Korean: A Comprehensive Grammar’, published by Routledge in early 2011. The point about pedagogical grammar is that it is not the same as linguistic grammar because they have different functions and uses. Pedagogical grammar typically requires rules that are definite, coherent, consistent,non-technical,cumulative and heuristic. Actual problems and topics at issue are discussed in the paper and the book’s table of contents is presented at the end of the paper

Comparing Automated Methods to Detect Explicit Content in Song Lyrics

International audienceThe Parental Advisory Label (PAL) is a warning label that is placed on audio recordings inrecognition of profanity or inappropriate references, with the intention of alerting parents of material potentially unsuitable for children.Since 2015, digital providers – such as iTunes,Spotify, Amazon Music and Deezer – also follow PAL guidelines and tag such tracks as “explicit”. Nowadays, such labelling is carried out mainly manually on voluntary basis, with the drawbacks of being time consuming and therefore costly, error prone and partly a subjective task. In this paper, we compare auto-mated methods ranging from dictionary-basedlookup to state-of-the-art deep neural networks to automatically detect explicit contents in English lyrics. We show that more complex models perform only slightly better on this task, and relying on a qualitative analysis of thedata, we discuss the inherent hardness and subjectivity of the task