Fostering Reading Skill on Narrative Text by Using Sticky Notes: Students’ Experiences in The Indonesian Higher Education Context

The present study aims to find out how the use of sticky notes can help EFL students to improve their skills in reading narrative texts. Using a qualitative approach, data were collected through semi-structured interviews taking a sample of 7 third-semester EFL students at an Indonesian higher education. Interview data in the form of implementation patterns of using sticky notes in narrative texts were explored to determine recommendations and produce research. The findings of this study from qualitative research indicate that provocative language and plots are major contributors to EFL students' difficulties in reading narrative texts. In addition, it also shows that EFL students use various reading comprehension strategies. Based on the results of this study, a new approach was found using sticky notes to read narrative texts. Most of the participants considered the use of sticky notes to be effective in improving reading skills. Although there were, several participants, stated that their use was less effective for reasons of time efficiency. The impact of this research is that a new method, namely sticky notes which are considered commonplace, can provide benefits in improving students' reading skills in English

Developing a multilayer semantic annotation scheme based on ISO standards for the visualization of a newswire corpus

In this paper, we describe the process of developing a multilayer semantic annotation scheme designed for extracting information from a European Portuguese corpus of news articles, at three levels, temporal, referential and semantic role labelling. The novelty of this scheme is the harmonization of parts 1, 4 and 9 of the ISO 24617 Language resource management - Semantic annotation framework. This annotation framework includes a set of entity structures (participants, events, times) and a set of links (temporal, aspectual, subordination, objectal and semantic roles) with several tags and attribute values that ensure adequate semantic and visual representations of news stories

A Narrative Sentence Planner and Structurer for Domain Independent, Parameterizable Storytelling

Storytelling is an integral part of daily life and a key part of how we share information and connect with others. The ability to use Natural Language Generation (NLG) to produce stories that are tailored and adapted to the individual reader could have large impact in many different applications. However, one reason that this has not become a reality to date is the NLG story gap, a disconnect between the plan-type representations that story generation engines produce, and the linguistic representations needed by NLG engines. Here we describe Fabula Tales, a storytelling system supporting both story generation and NLG. With manual annotation of texts from existing stories using an intuitive user interface, Fabula Tales automatically extracts the underlying story representation and its accompanying syntactically grounded representation. Narratological and sentence planning parameters are applied to these structures to generate different versions of the story. We show how our storytelling system can alter the story at the sentence level, as well as the discourse level. We also show that our approach can be applied to different kinds of stories by testing our approach on both Aesop’s Fables and first-person blogs posted on social media. The content and genre of such stories varies widely, supporting our claim that our approach is general and domain independent. We then conduct several user studies to evaluate the generated story variations and show that Fabula Tales’ automatically produced variations are perceived as more immediate, interesting, and correct, and are preferred to a baseline generation system that does not use narrative parameters

Developing a large semantically annotated corpus

International audienceWhat would be a good method to provide a large collection of semantically annotated texts with formal, deep semantics rather than shallow? We argue that a bootstrapping approach comprising state-of-the-art NLP tools for parsing and semantic interpretation, in combination with a wiki-like interface for collaborative annotation of experts, and a game with a purpose for crowdsourcing, are the starting ingredients for fulfilling this enterprise. The result is a semantic resource that anyone can edit and that integrates various phenomena, including predicate-argument structure, scope, tense, thematic roles, rhetorical relations and presuppositions, into a single semantic formalism: Discourse Representation Theory. Taking texts rather than sentences as the units of annotation results in deep semantic representations that incorporate discourse structure and dependencies. To manage the various (possibly conflicting) annotations provided by experts and non-experts, we introduce a method that stores " Bits of Wisdom " in a database as stand-off annotations