A Review of Research-Based Automatic Text Simplification Tools

In the age of knowledge, the democratisation of information facilitated through the Internet may not be as pervasive if written language poses challenges to particular sectors of the population. The objective of this paper is to present an overview of research-based automatic text simplification tools. Consequently, we describe aspects such as the language, language phenomena, language levels simplified, approaches, specific target populations these tools are created for (e.g. individuals with cognitive impairment, attention deficit, elderly people, children, language learners), and accessibility and availability considerations. The review of existing studies covering automatic text simplification tools is undergone by searching two databases: Web of Science and Scopus. The eligibility criteria involve text simplification tools with a scientific background in order to ascertain how they operate. This methodology yielded 27 text simplification tools that are further analysed. Some of the main conclusions reached with this review are the lack of resources accessible to the public, the need for customisation to foster the individual’s independence by allowing the user to select what s/he finds challenging to understand while not limiting the user’s capabilities and the need for more simplification tools in languages other than English, to mention a few.This research was conducted as part of the Clear-Text project (TED2021-130707B-I00), funded by MCIN/AEI/10.13039/501100011033 and European Union NextGenerationEU/PRTR

An authoring tool for decision support systems in context questions of ecological knowledge

Decision support systems (DSS) support business or organizational decision-making activities, which require the access to information that is internally stored in databases or data warehouses, and externally in the Web accessed by Information Retrieval (IR) or Question Answering (QA) systems. Graphical interfaces to query these sources of information ease to constrain dynamically query formulation based on user selections, but they present a lack of flexibility in query formulation, since the expressivity power is reduced to the user interface design. Natural language interfaces (NLI) are expected as the optimal solution. However, especially for non-expert users, a real natural communication is the most difficult to realize effectively. In this paper, we propose an NLI that improves the interaction between the user and the DSS by means of referencing previous questions or their answers (i.e. anaphora such as the pronoun reference in “What traits are affected by them?”), or by eliding parts of the question (i.e. ellipsis such as “And to glume colour?” after the question “Tell me the QTLs related to awn colour in wheat”). Moreover, in order to overcome one of the main problems of NLIs about the difficulty to adapt an NLI to a new domain, our proposal is based on ontologies that are obtained semi-automatically from a framework that allows the integration of internal and external, structured and unstructured information. Therefore, our proposal can interface with databases, data warehouses, QA and IR systems. Because of the high NL ambiguity of the resolution process, our proposal is presented as an authoring tool that helps the user to query efficiently in natural language. Finally, our proposal is tested on a DSS case scenario about Biotechnology and Agriculture, whose knowledge base is the CEREALAB database as internal structured data, and the Web (e.g. PubMed) as external unstructured information.This paper has been partially supported by the MESOLAP (TIN2010-14860), GEODAS-BI (TIN2012-37493-C03-03), LEGOLANGUAGE (TIN2012-31224) and DIIM2.0 (PROMETEOII/2014/001) projects from the Spanish Ministry of Education and Competitivity. Alejandro Maté is funded by the Generalitat Valenciana under an ACIF grant (ACIF/2010/298)

Event extraction of bacteria biotopes: a knowledge-intensive NLP-based approach

International audienceBackground: Bacteria biotopes cover a wide range of diverse habitats including animal and plant hosts, natural, medical and industrial environments. The high volume of publications in the microbiology domain provides a rich source of up-to-date information on bacteria biotopes. This information, as found in scientific articles, is expressed in natural language and is rarely available in a structured format, such as a database. This information is of great importance for fundamental research and microbiology applications (e.g., medicine, agronomy, food, bioenergy). The automatic extraction of this information from texts will provide a great benefit to the field

Genealogy Extraction and Tree Generation from Free Form Text

Genealogical records play a crucial role in helping people to discover their lineage and to understand where they come from. They provide a way for people to celebrate their heritage and to possibly reconnect with family they had never considered. However, genealogical records are hard to come by for ordinary people since their information is not always well established in known databases. There often is free form text that describes a person’s life, but this must be manually read in order to extract the relevant genealogical information. In addition, multiple texts may have to be read in order to create an extensive tree. This thesis proposes a novel three part system which can automatically interpret free form text to extract relationships and produce a family tree compliant with GED- COM formatting. The first subsystem builds an extendable database of genealogical records that are systematically extracted from free form text. This corpus provides the tagged data for the second subsystem, which trains a Naı̈ve Bayes classifier to predict relationships from free form text by examining the types of relationships for pairs of entities and their associated feature vectors. The last subsystem accumulates extracted relationships into family trees. When a multiclass Naı̈ve Bayes classifier is used, the proposed system achieves an accuracy of 54%. When binary Naı̈ve Bayes classifiers are used, the proposed system achieves accuracies of 69% for the child to parent relationship classifier, 75% for the spousal relationship classifier, and 73% for the sibling relationship classifier

Non-EFL Students’ Perception of Grammar and Their Ability in Understanding Basic Grammar

This study describes the students’ perception of grammar and to know their ability in understanding basic grammar. This research is descriptive qualitative. The analysis shows that students like learning English grammar because grammar is a rule or guideline related to English proficiency. But a lot of grammar material must be learned because it is very complicated, complex, and interrelated with other materials. Learning grammar is important for them in mastering writing, speaking, listening, reading, and vocabulary. After learning grammar, the students agree that the lecturer teaches grammar material in a fun way, explains grammar material well accompanied by examples and practice, and then gives assignments as understanding evaluations every meeting. The students can understand grammar lessons in English although the grammar learned in college is more complex than in high school, they do not have any difficulty understanding the material on campus. Grammar helps students to able to communicate orally and written in English better, but they still need to learn more grammar to improve their English skills. However, the result of the tests shows something different from their positive perceptions after learning grammar. The average score is 66.86 from 100 points, the median is 71 from 100 points, and the range from the lowest score of 33 up to 91 points score (correct answer) as the highest score. Further research, of course, still needs to be done to find out the reasons why students' grammar skills show an unsatisfactory average

America\u27s Quandary-- Masking Injustice: Ideological Analyses of America\u27s Moves Towards its Promise | A Pedagogical Primer on Rhetoric

AMERICA’S QUANDARY— MASKING INJUSTICE: IDEOLOGICAL ANALYSES OF AMERICA’S MOVES TOWARDS ITS PROMISE | A PEDAGOGICAL PRIMER ON RHETORIC by RONALD JERRY WALKER Under the Direction of George Pullman, PhD, and Elizabeth Sanders Lopez, PhD ABSTRACT Rhetoric, persuasive discourse, and rhetorical analysis, art and science of rhetorical text scrutiny, are invaluable aspects of composition pedagogy. Rhetoric commands our world. This dissertation project manifests four features. First, it reveals America’s promise through rhetorical artifact texts. Second, the project presents an academic investigation—America’s moves towards its promise. Third, it recounts the continuing injustices suffered by women and peoples of color, all hidden behind (rhetorical) masks, that continue to plague America. And fourth, this collection altogether serves as a pedagogical primer on rhetoric. Founding documents and public monuments serve as a ruse that masks injustice and inequality. This is America’s quandary, a reality that unfortunately escapes journalistic focus. Masks enable the American hegemony of sexism, racism, homophobia, xenophobia, and classism to thrive. This nation’s affluent “founders” completely ignored and erased the vast majority of peoples co-inhabiting our boundless lands—millions of indigenous Native American nations; women, not mentioned anywhere among America’s founding documents; abducted African (forced) laborers commanded to toil generational lives, as chattel; and poor whites. Later immigrants, especially peoples of color, would also be denied their “liberty and justice for all.” Today, the USA is World Number One—in obesity, in opioid addiction, in female prison incarceration, in male prison incarceration, in military defense spending, in military weaponry (international spread), and in war (today Afghanistan, Syria, Iraq, Yemen, Somalia, Libya, Niger). And in international intrigue (arrogance). America’s quandary is our lack of universal healthcare, the antiquated Electoral College, the rising 1%, the shrinking middle class, the widening gap between America’s rich and poor, and our obsessive desire to police and command the world. This project interrogates rhetoric “to unmask and demystify” America’s rhetorical hegemony of disadvantage and inequality; while America faces a bleak future. We English teachers are First Responders for our culture. Our democratic republic must have—to survive—a committed populace of engaged citizens whose critical thinking, analytical reasoning, and civic responsibility can invigorate American culture. If We are successful, America will be successful; if We fail, America will fail. Perhaps if We could just make America better, all would work out. INDEX WORDS: Rhetorical analysis, Rhetorical devices, Critical thinking, Argument essa