TempTabQA: Temporal Question Answering for Semi-Structured Tables

Semi-structured data, such as Infobox tables, often include temporal information about entities, either implicitly or explicitly. Can current NLP systems reason about such information in semi-structured tables? To tackle this question, we introduce the task of temporal question answering on semi-structured tables. We present a dataset, TempTabQA, which comprises 11,454 question-answer pairs extracted from 1,208 Wikipedia Infobox tables spanning more than 90 distinct domains. Using this dataset, we evaluate several state-of-the-art models for temporal reasoning. We observe that even the top-performing LLMs lag behind human performance by more than 13.5 F1 points. Given these results, our dataset has the potential to serve as a challenging benchmark to improve the temporal reasoning capabilities of NLP models.Comment: EMNLP 2023(Main), 23 Figures, 32 Table

Topic-based analysis for technology intelligence

University of Technology Sydney. Faculty of Engineering and Information Technology.Since the past several decades, scientific literature, patents and other semi-structured technology indicators have been generating and accumulating at a very rapid rate. Their growth provides a wealth of information regarding technology development in both the public and private domain. However, it has also caused increasingly severe information overload problems whereby researchers, analysts and decision makers are not able to read, summarize and understand massive technical documents and records manually. The concept and tools of technology intelligence aims to handle this issue. In the current technology intelligence research, one of the big challenges is that, the frameworks and applications of existing technology intelligence conducted semantic content analysis and temporal trend estimation separately, lacking a comprehensive perspective on trend analysis of the detailed content within an area. In addition, existing research of technology intelligence is mainly constructed on the fundamentals of semantic properties of the semi-structured technology indicators; however, single keywords and their ranking alone, are too general or ambiguous to represent complex concepts and their corresponding temporal patterns. Thirdly, systematic post-processing, forecasting and evaluation on both content analysis and trend identification outputs are still in great demand, for diverse and flexible technological decision support and opportunity discovery. This research aims to handle these three challenges in both theoretical and practical aspects. It first quantitatively defines and presents temporal characteristics and semantic properties of typical semi-structured technology indicators. Then this thesis proposes a framework of topic-based technology intelligence, with three main functionalities, including data-driven trend identification, topic discovery and comprehensive topic evaluation, to synthetically process and analyse technological publication count sequence, textual data and metadata of target technology indicators. To achieve the three functionalities, this research proposes an empirical technology trend analysis method to extract temporal trend turning points and trend segments, which help with producing a more reasonable time-based measure; a topic-based technological forecasting method to first discover and characterize the semantic knowledge underlying in massive textual data of technology indicators, meanwhile estimating the future trends of the discovered topics; a comprehensive topic evaluation method that links metadata and discovered topics, to provide integrated landscape and technological insight in depth. In order to demonstrate the proposed topic-based technology intelligence framework and all the related methods, this research presents case studies with both patents and scientific literature. Experimental results on Australian patents, United States patents and scientific papers from Web of Science database, showed that the proposed framework and methods are well-suited in dealing with semi-structured technology indicators analysis, and can provide valuable topic-based knowledge to facilitate further technological decision making or opportunity discovery with good performance

Being in Time : New Public Management, Academic Librarians, and the Temporal Labor of Pink-Collar Public Service Work

Time is a site of power, one that enacts particular subjectivities and relationships. In the workplace, time enables and constrains performance, attitudes, and behaviors. In this qualitative research study, I examine the impact of the values and practices of new public management on academic librarians’ experiences of time when engaged in pink-collar public service (reference and information literacy) work. Data gathered during semi-structured interviews with twenty-four public service librarians in Canadian public research-intensive universities, members of the U15 Group, serve as a site of analysis for this study. Interview data were first analyzed using thematic analysis (Braun and Clarke 2006) within a constructionist framework. Sharma’s (2014) theory of power-chronography—time as power—was then used as an analytical framework. Findings suggest that, in keeping with research on the temporal experiences of faculty, academic librarians’ temporal labor is structured and controlled by the logics and institutional arrangements of new public management. Moreover, like their faculty counterparts, academic librarians experience temporal intensification and acceleration. However, as marginal educators and members of a feminized profession, librarians also encounter “recalibration” (Sharma 2014), the need to modify the tempo of their own labor to be “in time” with the dominant temporalities of faculty and students

Occupation, mental illness and medium security: A study of occupational engagement in two forensic regional secure units

Research investigating occupational experience among people with mental illness has highlighted their difficulties in selecting, organising, valuing, enjoying and competently performing occupations. Although occupational therapy literature consistently identifies environmental factors as key in facilitating successful and valued engagement, few authors have studied the implications of detention in secure mental health settings for this population. This study investigated the occupational experiences of five people with schizophrenia in two forensic regional secure units. Quantitative and qualitative methodologies were used, with semi-structured interviews adding depth and subjectivity to Occupational Questionnaire (Smith et al 1986) responses. The quantitative data were analysed using non-parametric analysis, with content analysis applied to the qualitative data. Time-use was characterised predominantly by engagement in passive leisure and rest occupations. This reflects the findings of both inpatient and community-based studies elsewhere and suggests that mental illness is a common factor influencing time-use. The participants chose occupations based on expectations of enjoyment and success, and associations with independence and normality. Significant correlations were found between perceived competence, value and enjoyment (p<0.01), and the participants were more likely to enjoy self-chosen occupations (p<0.05). Forensic occupational therapists must use evidence to optimise resources and deliver interventions that facilitate choice and autonomy and reflect individual needs. Further research with larger samples and longitudinal methodologies will facilitate generalisation and establish temporal perspective