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Within the context of Information Extraction (IE), relation extraction is oriented towards identifying a variety of relation phrases and their arguments in arbitrary sentences. In this paper, we present a clause-based framework for information extraction in textual documents. Our framework focuses on two important challenges in information extraction: 1) Open Information Extraction and (OIE), and 2) Relation Extraction (RE). In the plethora of research that focus on the use of syntactic and dependency parsing for the purposes of detecting relations, there has been increasing evidence of incoherent and uninformative extractions. The extracted relations may even be erroneous at times and fail to provide a meaningful interpretation. In our work, we use the English clause structure and clause types in an effort to generate propositions that can be deemed as extractable relations. Moreover, we propose refinements to the grammatical structure of syntactic and dependency parsing that help reduce the number of incoherent and uninformative extractions from clauses. In our experiments both in the open information extraction and relation extraction domains, we carefully evaluate our system on various benchmark datasets and compare the performance of our work against existing state-of-the-art information extraction systems. Our work shows improved performance compared to the state-of-the-art techniques. 相似文献
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Hoang Loc Phuoc Le Hieu Thanh Van Tran Hung Phan Thanh Chi Vo Duc Minh Le Phuong Anh Nguyen Dung The Pong-inwong Chakrit 《Education and Information Technologies》2022,27(3):4007-4035
Education and Information Technologies - Peer assessment has an important role in teaching and learning nowadays. However, the existing techniques tend to be limited due to a lack of a suitable... 相似文献
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Inverted Index Compression Using Word-Aligned Binary Codes 总被引：3，自引：1，他引：3
We examine index representation techniques for document-based inverted files, and present a mechanism for compressing them using word-aligned binary codes. The new approach allows extremely fast decoding of inverted lists during query processing, while providing compression rates better than other high-throughput representations. Results are given for several large text collections in support of these claims, both for compression effectiveness and query efficiency. 相似文献
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Relation extraction aims at finding meaningful relationships between two named entities from within unstructured textual content. In this paper, we define the problem of information extraction as a matrix completion problem where we employ the notion of universal schemas formed as a collection of patterns derived from open information extraction systems as well as additional features derived from grammatical clause patterns and statistical topic models. One of the challenges with earlier work that employ matrix completion methods is that such approaches require a sufficient number of observed relation instances to be able to make predictions. However, in practice there is often insufficient number of explicit evidence supporting each relation type that could be used within the matrix model. Hence, existing work suffer from a low recall. In our work, we extend the work in the state of the art by proposing novel ways of integrating two sets of features, i.e., topic models and grammatical clause structures, for alleviating the low recall problem. More specifically, we propose that it is possible to (1) employ grammatical clause information from textual sentences to serve as an implicit indication of relation type and argument similarity. The basis for this is that it is likely that similar relation types and arguments are observed within similar grammatical structures, and (2) benefit from statistical topic models to determine similarity between relation types and arguments. We employ statistical topic models to determine relation type and argument similarity based on their co-occurrence within the same topics. We have performed extensive experiments based on both gold standard and silver standard datasets. The experiments show that our approach has been able to address the low recall problem in existing methods, by showing an improvement of 21% on recall and 8% on f-measure over the state of the art baseline. 相似文献
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Ben Baumfalk Devarati Bhattacharya Tina Vo Cory Forbes Laura Zangori Christina Schwarz 《科学教学研究杂志》2019,56(5):570-597
Developing scientific literacy about water systems is critical for K-12 students. However, even with opportunities to build knowledge about the hydrosphere in elementary classrooms, early learners may struggle to understand the water cycle (Forbes et al., 2015 ; Gunckel et al., 2012 ; Zangori et al., 2015 ; Zangori et al., 2017 ). Scientific modeling affords opportunities for students to develop representations, make their ideas visible, and generate model-based explanations for complex natural systems like the water cycle. This study describes a comprehensive evaluation of a 5-year, design-based research project focused on the development, implementation, revision, and testing of an enhanced, model-centered version of the Full Option Science System (FOSS) Water (2005) unit in third grade classrooms. Here, we build upon our previous work (Forbes et al., 2015 a; b; Vo et al., 2015 ; Zangori et al., 2015 ; Zangori et al., 2017 ) by conducting a comparative analysis of student outcomes in two sets of classrooms: (1) one implementing the modeling-enhanced version of the FOSS Water unit developed by the research team (n = 6), and 2) another using the standard, unmodified version of the same curricular unit (n = 5). Results demonstrate that teachers in both conditions implemented the two versions of the curriculum with relative fidelity. On average, students exposed to the modeling-enhanced version of the curriculum showed greater gains in their model-based explanations for the hydrosphere. Engagement in scientific modeling allowed students to articulate hydrologic phenomena by (1) identifying various elements that constitute the hydrosphere, (2) describing how these elements influenced the movement of water in the hydrosphere, and (3) demonstrating underlying processes that govern the movement of water in the hydrosphere. 相似文献
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Research in Science Education - This sequential explanatory mixed methods study (quant + QUAL) examined elementary preservice teachers’ conceptions of teaching engineering. Participants... 相似文献
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Tina Vo Cory T. Forbes Laura Zangori Christina V. Schwarz 《International Journal of Science Education》2013,35(15):2411-2432
Elementary teachers play a crucial role in supporting and scaffolding students’ model-based reasoning about natural phenomena, particularly complex systems such as the water cycle. However, little research exists to inform efforts in supporting elementary teachers’ learning to foster model-centered, science learning environments. To address this need, we conducted an exploratory multiple-case study using qualitative research methods to investigate six 3rd-grade teachers’ pedagogical reasoning and classroom instruction around modeling practices (construct, use, evaluate, and revise) and epistemic considerations of scientific modeling (generality/abstraction, evidence, mechanism, and audience). Study findings show that all teachers emphasized a subset of modeling practices—construction and use—and the epistemic consideration of generality/abstraction. There was observable consistency between teachers’ articulated conceptions of scientific modeling and their classroom practices. Results also show a subset of the teachers more strongly emphasized additional epistemic considerations and, as a result, better supported students to use models as sense-making tools as well as representations. These findings provide important evidence for developing elementary teacher supports to scaffold students’ engagement in scientific modeling. 相似文献
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European Journal of Psychology of Education - The purpose of this study is to explore students’ motivation towards science learning at different grade levels and to investigate whether... 相似文献
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