Extracting Temporal and Causal Relations between Events

Structured information resulting from temporal information processing is crucial for a variety of natural language processing tasks, for instance to generate timeline summarization of events from news documents, or to answer temporal/causal-related questions about some events. In this thesis we present a framework for an integrated temporal and causal relation extraction system. We first develop a robust extraction component for each type of relations, i.e. temporal order and causality. We then combine the two extraction components into an integrated relation extraction system, CATENA---CAusal and Temporal relation Extraction from NAtural language texts---, by utilizing the presumption about event precedence in causality, that causing events must happened BEFORE resulting events. Several resources and techniques to improve our relation extraction systems are also discussed, including word embeddings and training data expansion. Finally, we report our adaptation efforts of temporal information processing for languages other than English, namely Italian and Indonesian.Comment: PhD Thesi

Learning Sentence-internal Temporal Relations

In this paper we propose a data intensive approach for inferring sentence-internal temporal relations. Temporal inference is relevant for practical NLP applications which either extract or synthesize temporal information (e.g., summarisation, question answering). Our method bypasses the need for manual coding by exploiting the presence of markers like after", which overtly signal a temporal relation. We first show that models trained on main and subordinate clauses connected with a temporal marker achieve good performance on a pseudo-disambiguation task simulating temporal inference (during testing the temporal marker is treated as unseen and the models must select the right marker from a set of possible candidates). Secondly, we assess whether the proposed approach holds promise for the semi-automatic creation of temporal annotations. Specifically, we use a model trained on noisy and approximate data (i.e., main and subordinate clauses) to predict intra-sentential relations present in TimeBank, a corpus annotated rich temporal information. Our experiments compare and contrast several probabilistic models differing in their feature space, linguistic assumptions and data requirements. We evaluate performance against gold standard corpora and also against human subjects

PersoNER: Persian named-entity recognition

© 1963-2018 ACL. Named-Entity Recognition (NER) is still a challenging task for languages with low digital resources. The main difficulties arise from the scarcity of annotated corpora and the consequent problematic training of an effective NER pipeline. To abridge this gap, in this paper we target the Persian language that is spoken by a population of over a hundred million people world-wide. We first present and provide ArmanPerosNERCorpus, the first manually-annotated Persian NER corpus. Then, we introduce PersoNER, an NER pipeline for Persian that leverages a word embedding and a sequential max-margin classifier. The experimental results show that the proposed approach is capable of achieving interesting MUC7 and CoNNL scores while outperforming two alternatives based on a CRF and a recurrent neural network

Models of atypical development must also be models of normal development

Functional magnetic resonance imaging studies of developmental disorders and normal cognition that include children are becoming increasingly common and represent part of a newly expanding field of developmental cognitive neuroscience. These studies have illustrated the importance of the process of development in understanding brain mechanisms underlying cognition and including children ill the study of the etiology of developmental disorders

Relationship between Reframing Strategies Adopted by the Translator and the Attitude of the Reader toward the Translation: A Case Study of the Book "The Grass is Singing" by "Doris Lessing"

Since language is production and translation is reproduction, there are always slight changes in representing intentions. These changes may be greater in translation. Most changes occur unconsciously and unintentionally but sometimes these changes are consciously, intentionally and purposefully. Reframing is a strategy in narrative theory that is used to change some dimensions of translated text. In this paper the researcher was an attempt to investigate the ideological manipulation under Baker’s renarrative theory conducted within a descriptive framework through comparing a parallel text in English and Persian. In this paper, "The grass is singing" by "Doris Lessing", translated by Dr. Zahra Karimi was analyzed to see the changes that have occurred in translation. The analysis revealed that the instances of reframing are numerous but often overlapping. The most common reframing strategy was selective appropriation which, however, usually resulted in occurrences of other reframing strategies

Syntactic Object Representations Found in Awgni Sentences

Teachers and students in Injibara college were unable to understand syntactic object representations found in Awgni sentences. The motivation of this research was designed to fill the gap by analyzing syntactic object representations found in Awgni sentences. Henceforth, the objective of the study was to examine the Syntactic Object representations found within Awgni sentences classified by their function. A descriptive analysis was employed to interpret the sentence structures. The data were collected from the native speakers of Awi people (7 males, 6 females) based on their day-to-day outgoing acts, and from different texts. By purposive sampling, 23 sentences were selected, arranged, and described. The method of data analysis applied was Labeling Algorithm {XP, YP}. Thus, raising XP Syntactic Objects has been modified and consequently, there is only one visible head. The result indicated that Awgni sentences in terms of their forms, forming, a causal relationship they contain were different. On the other hand, each sentence structure shares Syntactic Object representations that include NPs, VPs, DPs, PPs, ADVPs, and APs. Finally, the study recommended further research on how (LA) {H, XP}, and {X, Y} works to describe the label of every Syntactic Object representations found within sentence structures in Awgni

The linguistic construction of business reasoning: Towards a language-based model of decision-making in undergraduate business

This thesis reports on research whose aim is to arrive at a linguistically theorised understanding of the process of decision-making in undergraduate business studies. The use of ‘real-life’ tasks such as country reports – the major assessment task of the interdisciplinary unit Business in the Global Environment at a metropolitan Australian university – is intended to prepare students for the skills of ‘problem-solving’, ‘decision-making’ and professional report writing in international business environments. However, as indicated by the large number of students failing this task, few students possess the sophisticated linguistic resources necessary to build the generic complexity and persuasive rhetoric this high-stakes task demands. This study is concerned with identifying the linguistic demands of demonstrating decision-making in country reports. Current modelling of ‘big texts’ in SFL (Martin, 1994, 1995) is insufficient for understanding longer texts stretching across the many pages tertiary students are generally required to write. This thesis will show through fine-grained linguistic analyses of High Distinction student assignments that not all ‘big texts’ are macrogenres made up of elemental genre complexes and illustrate that embedded genres play a fundamental role in enabling texts of the length of business country reports to grow bigger than a page. Drawing on discourse semantics (Martin, 1992; Martin & Rose, 2007; Martin & White, 2005), this thesis also will also show how business reasoning is construed in undergraduate business reports through different types of grammatical structures and how successful student writers construct cause-effect relations and three major types of rhetorical moves in these texts. By making visible the academically valued meanings by which skillful writers demonstrate the process of decision-making in undergraduate business country reports, this research has pedagogical implications for academic literacy interventions aimed at making explicit the basis of achievement in business studies. It is hoped that this study will open up future research directions for the continued study of knowledge-building in undergraduate business studies

Introduction: an overview of the acquisition of reference

Language is a social tool that allows us to speak to others about the world. In doing so we need words that pick out those entities that we want to talk about. Linguistic expressions that identify such entities are known as referential or referring expressions, including proper names (Laura), natural kind terms (water, gold, tiger), indexicals (you, I, she), and definite descriptions (the dog, the smallest positive number). The mechanisms of reference have been the subject of intense speculation, and the debate over descriptive (Frege 1892/1948; Searle, 1958) vs. causal (Kripke, 1972/1980) or hybrid theories of reference (Evans, 1973) is still rife in the semantics literature (Genone & Lombrozo, 2012; Lam, 2010; Martí, 2014). Whatever the theoretical approach to reference, from a developmental perspective the three key questions are the following: What is the trajectory of language learners’ comprehension and production of referential expressions? To what extent, and in which contexts, do children abide by the same linguistic constraints as adults in their referential choices? How do cross-linguistic differences shape the process of referential choice acquisition