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On the Representation of Physical Quantities in Natural Language Text
- Proceedings of the Twenty-sixth Annual Meeting of the Cognitive Science Society
, 2004
"... In this paper we investigate the forms in which quantity information can appear in written natural language. Our focus is on physical quantities found in descriptions of physical processes, such as expansion, movement, or transfer. Using Qualitative Process Theory as our underlying formalism, we sho ..."
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In this paper we investigate the forms in which quantity information can appear in written natural language. Our focus is on physical quantities found in descriptions of physical processes, such as expansion, movement, or transfer. Using Qualitative Process Theory as our underlying formalism, we show how information extracted from natural language text corresponds to the five constituents of physical quantities. The results of this analysis can be used for the creation of interpretation rules and extraction patterns in NL systems.
Causal systems categories: Differences in novice and expert categorization of causal phenomena
- Cognitive Science
, 2012
"... Abstract We investigated the understanding of causal systems categories-categories defined by common causal structure rather than by common domain content-among college students. We asked students who were either novices or experts in the physical sciences to sort descriptions of real-world phenome ..."
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Abstract We investigated the understanding of causal systems categories-categories defined by common causal structure rather than by common domain content-among college students. We asked students who were either novices or experts in the physical sciences to sort descriptions of real-world phenomena that varied in their causal structure (e.g., negative feedback vs. causal chain) and in their content domain (e.g., economics vs. biology). Our hypothesis was that there would be a shift from domain-based sorting to causal sorting with increasing expertise in the relevant domains. This prediction was borne out: The novice groups sorted primarily by domain and the expert group sorted by causal category. These results suggest that science training facilitates insight about causal structures.
Steps towards a 2nd generation learning by reading system
, 2009
"... Learning by reading is an important scientific problem because it requires modeling a wide range of human abilities. It also could break the knowledge engineering bottleneck, enabling the bootstrapping of intelligent systems via interaction with people using natural language. This paper outlines our ..."
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Cited by 1 (1 self)
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Learning by reading is an important scientific problem because it requires modeling a wide range of human abilities. It also could break the knowledge engineering bottleneck, enabling the bootstrapping of intelligent systems via interaction with people using natural language. This paper outlines our progress on creating a 2nd generation learning by reading system, focusing on three main areas: Multimodal knowledge capture, reasoning for L understanding and learning, and analogical dialogue acts.
Qualitative reasoning in the education of deaf students: scientific education and acquisition of Portuguese as a second language
"... Brazilian educational system is faced with the task of promoting deaf people educational rights. Presently, the deaf are integrated in the classroom along with hearing students. Qualitative Reasoning may provide tools to support Portuguese acquisition in the context of the development of scientific ..."
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Brazilian educational system is faced with the task of promoting deaf people educational rights. Presently, the deaf are integrated in the classroom along with hearing students. Qualitative Reasoning may provide tools to support Portuguese acquisition in the context of the development of scientific concepts. This study describes an experiment with eight deaf students being exposed to three articulate qualitative models organized in gradual levels of complexity. Questionnaires were used to assess ther students ’ ability of expressing ideas in written Portuguese using the ontology provided by the models. An interesting result was that five students were consistent in the ability of recognizing objects and processes, build up causal chains and apply them to a given situation, assessing derivative values of quantities and
SEE PROFILE
, 2014
"... On the acquisition of abstract knowledge: Structural alignment and explication in learning causal system categories ..."
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On the acquisition of abstract knowledge: Structural alignment and explication in learning causal system categories
Machine Reading as a Cognitive Science Research Instrument
"... We describe how we are using natural language techniques to develop systems that can automatically encode a range of input materials for cognitive simulations. We start by summarizing this type of problem, and the components we are using. We then describe three projects that are using this common in ..."
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We describe how we are using natural language techniques to develop systems that can automatically encode a range of input materials for cognitive simulations. We start by summarizing this type of problem, and the components we are using. We then describe three projects that are using this common infrastructure: learning from multimodal materials, modeling decision making in moral dilemmas, and modeling conceptual change in development.
Capturing QP-relevant Information from Natural Language Text
"... People can learn about the physical world from textbooks and develop an understanding of physical phenomena from simple descriptions. As part of our ongoing investigation of the extraction and representation of knowledge about physical processes found in natural language text, we describe a natural ..."
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People can learn about the physical world from textbooks and develop an understanding of physical phenomena from simple descriptions. As part of our ongoing investigation of the extraction and representation of knowledge about physical processes found in natural language text, we describe a natural language system that captures information about instances of physical processes from paragraph-sized descriptions through a deep semantic interpretation process as a set of interconnected frame structures.
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"... Towards a qualitative model of everyday political reasoning Everyday political reasoning seems to have many properties in common with everyday physical reasoning: it involves continuous parameters, numerical values are typically unavailable, and causal reasoning about qualitatively distinct behavior ..."
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Towards a qualitative model of everyday political reasoning Everyday political reasoning seems to have many properties in common with everyday physical reasoning: it involves continuous parameters, numerical values are typically unavailable, and causal reasoning about qualitatively distinct behaviors is important. Can the techniques developed by the QR community be used to develop qualitative models of everyday political reasoning? This paper explores that question, using understanding texts about world history and current events as a focusing task. We outline some of the ontological issues involved, including modeling of emotions. We dissect a sample text to illustrate how QR ideas can be applied to understanding it, and discuss a largescale corpus analysis in progress. Our conclusion is that QR techniques show promise in capturing important aspects of everyday political reasoning.
Analogy Causal learning Categorization Education
, 2014
"... and explication in learning causal system categories ..."
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unknown title
"... Everyday political reasoning seems to have many properties in common with everyday physical rea-soning: it involves continuous parameters, numeri-cal values are typically unavailable, and causal rea-soning about qualitatively distinct behaviors is im-portant. Can the techniques developed by the QR c ..."
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Everyday political reasoning seems to have many properties in common with everyday physical rea-soning: it involves continuous parameters, numeri-cal values are typically unavailable, and causal rea-soning about qualitatively distinct behaviors is im-portant. Can the techniques developed by the QR community be used to develop qualitative models of everyday political reasoning? This paper ex-plores that question, using understanding texts about world history and current events as a focus-ing task. We outline some of the ontological issues involved, including modeling of emotions. We dissect a sample text to illustrate how QR ideas can be applied to understanding it, and discuss a large-scale corpus analysis in progress. Our conclusion is that QR techniques show promise in capturing important aspects of everyday political reasoning.
