Native and non-native speakers of English in summarising expository texts

This study examines how native and non-native English speakers summarise expository texts. It investigates if there is any difference in quality between the summaries produced by two groups of students; namely native speakers of English, who acquire the language in early childhood and have their education (from kindergarten / grade 1 to high school) in English, and non-native speakers, who acquire the language in an ESL/EFL context. The sample consisted of seventy undergraduates from a private Malaysian university, comprising thirty-five native and thirty-five non-native speakers of English. Data for the study include summaries by students, response to teacher and student questionnaires as well as interviews with both teachers and students. The results of the study revealed that there was a significant difference in the quality of summaries of native and non-native English speakers in expository text

Extracting Formal Models from Normative Texts

We are concerned with the analysis of normative texts - documents based on the deontic notions of obligation, permission, and prohibition. Our goal is to make queries about these notions and verify that a text satisfies certain properties concerning causality of actions and timing constraints. This requires taking the original text and building a representation (model) of it in a formal language, in our case the C-O Diagram formalism. We present an experimental, semi-automatic aid that helps to bridge the gap between a normative text in natural language and its C-O Diagram representation. Our approach consists of using dependency structures obtained from the state-of-the-art Stanford Parser, and applying our own rules and heuristics in order to extract the relevant components. The result is a tabular data structure where each sentence is split into suitable fields, which can then be converted into a C-O Diagram. The process is not fully automatic however, and some post-editing is generally required of the user. We apply our tool and perform experiments on documents from different domains, and report an initial evaluation of the accuracy and feasibility of our approach.Comment: Extended version of conference paper at the 21st International Conference on Applications of Natural Language to Information Systems (NLDB 2016). arXiv admin note: substantial text overlap with arXiv:1607.0148

A Survey of Paraphrasing and Textual Entailment Methods

Paraphrasing methods recognize, generate, or extract phrases, sentences, or longer natural language expressions that convey almost the same information. Textual entailment methods, on the other hand, recognize, generate, or extract pairs of natural language expressions, such that a human who reads (and trusts) the first element of a pair would most likely infer that the other element is also true. Paraphrasing can be seen as bidirectional textual entailment and methods from the two areas are often similar. Both kinds of methods are useful, at least in principle, in a wide range of natural language processing applications, including question answering, summarization, text generation, and machine translation. We summarize key ideas from the two areas by considering in turn recognition, generation, and extraction methods, also pointing to prominent articles and resources.Comment: Technical Report, Natural Language Processing Group, Department of Informatics, Athens University of Economics and Business, Greece, 201

Evaluating prose style transfer with the Bible

In the prose style transfer task a system, provided with text input and a target prose style, produces output which preserves the meaning of the input text but alters the style. These systems require parallel data for evaluation of results and usually make use of parallel data for training. Currently, there are few publicly available corpora for this task. In this work, we identify a high-quality source of aligned, stylistically distinct text in different versions of the Bible. We provide a standardized split, into training, development and testing data, of the public domain versions in our corpus. This corpus is highly parallel since many Bible versions are included. Sentences are aligned due to the presence of chapter and verse numbers within all versions of the text. In addition to the corpus, we present the results, as measured by the BLEU and PINC metrics, of several models trained on our data which can serve as baselines for future research. While we present these data as a style transfer corpus, we believe that it is of unmatched quality and may be useful for other natural language tasks as well

Comparison and Adaptation of Automatic Evaluation Metrics for Quality Assessment of Re-Speaking

Re-speaking is a mechanism for obtaining high quality subtitles for use in live broadcast and other public events. Because it relies on humans performing the actual re-speaking, the task of estimating the quality of the results is non-trivial. Most organisations rely on humans to perform the actual quality assessment, but purely automatic methods have been developed for other similar problems, like Machine Translation. This paper will try to compare several of these methods: BLEU, EBLEU, NIST, METEOR, METEOR-PL, TER and RIBES. These will then be matched to the human-derived NER metric, commonly used in re-speaking.Comment: Comparison and Adaptation of Automatic Evaluation Metrics for Quality Assessment of Re-Speaking. arXiv admin note: text overlap with arXiv:1509.0908

Plagiarism in philosophy: prevention better than cure

[Introduction] Plagiarism more common than thought in student essays’ would make a good headline. Recent research suggests that students admit to much more plagiarism and other forms of cheating than teachers generally suspect, and it is widely believed that the problem is increasing as a result of the internet. The solution is to use a range of techniques to get the thought back into student essay writing, and to take more active steps to spot when this has not happened

Researching the Use of Dictionary by Students of English Literature Department at Jenderal Soedirman University

Dictionaries are recommnded as a useful tool when learning EFL because it gives information of the language about many aspects like, phonology, morphology, syntax, and semantics. Nevertheless, EFL practionaires rarely pay attention to the dictionary used by the students. The article focuses on the investigation about types of dictionaries used, the frequency of dictionary use, and the lexical information examined. Respondents were students of English Literature Department, Jenderal Soedirman University. Data were taken from questionnaires. The result showed that students did not have any special instruction on how to make full use of the dictionaries. The respondents favored bilingual dictionaries over monolingual dictionaries. Respondents saw that pronunciation, usage, and examples were considered as a secondary importance

Specifying Logic Programs in Controlled Natural Language

Writing specifications for computer programs is not easy since one has to take into account the disparate conceptual worlds of the application domain and of software development. To bridge this conceptual gap we propose controlled natural language as a declarative and application-specific specification language. Controlled natural language is a subset of natural language that can be accurately and efficiently processed by a computer, but is expressive enough to allow natural usage by non-specialists. Specifications in controlled natural language are automatically translated into Prolog clauses, hence become formal and executable. The translation uses a definite clause grammar (DCG) enhanced by feature structures. Inter-text references of the specification, e.g. anaphora, are resolved with the help of discourse representation theory (DRT). The generated Prolog clauses are added to a knowledge base. We have implemented a prototypical specification system that successfully processes the specification of a simple automated teller machine.Comment: 16 pages, compressed, uuencoded Postscript, published in Proceedings CLNLP 95, COMPULOGNET/ELSNET/EAGLES Workshop on Computational Logic for Natural Language Processing, Edinburgh, April 3-5, 199