The Basic Formal Ontology (BFO) class continuant fiat boundary and its subclasses, including fiat surface, are not heavily axiomatized; they have elucidations, not definitions; and the meanings of these elucidations are poorly captured by the relevant BFO axioms. This paper is an effort to make progress in these respects for fiat surface. We identify a range of desiderata for a BFO-conformant view of fiat surface, argue that the GitHub does not satisfy them, argue that the view of fiat surfaces in Arp et al. (2015) does a better job, and supplement that view in ways that do a still better job. Our discussion allows us to, inter alia, present a number of axioms relevant to our topic worthy of consideration for inclusion in BFO or dependent ontologies in specific domains and for specific purposes.
{"title":"Fiat Surfaces in the Basic Formal Ontology.","authors":"Michael Rabenberg, Werner Ceusters","doi":"10.3233/FAIA241313","DOIUrl":"10.3233/FAIA241313","url":null,"abstract":"<p><p>The Basic Formal Ontology (BFO) class <i>continuant fiat boundary</i> and its subclasses, including <i>fiat surface</i>, are not heavily axiomatized; they have elucidations, not definitions; and the meanings of these elucidations are poorly captured by the relevant BFO axioms. This paper is an effort to make progress in these respects for <i>fiat surface</i>. We identify a range of desiderata for a BFO-conformant view of <i>fiat surface</i>, argue that the GitHub does not satisfy them, argue that the view of fiat surfaces in Arp et al. (2015) does a better job, and supplement that view in ways that do a still better job. Our discussion allows us to, <i>inter alia</i>, present a number of axioms relevant to our topic worthy of consideration for inclusion in BFO or dependent ontologies in specific domains and for specific purposes.</p>","PeriodicalId":90829,"journal":{"name":"Formal ontology in information systems : proceedings of the ... International Conference. FOIS (Conference)","volume":"394 ","pages":"268-282"},"PeriodicalIF":0.0,"publicationDate":"2024-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11656323/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142866553","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
SNOMED CT is a large concept-based terminology designed according to epistemic, semantic and pragmatic principles relevant to clinicians. Its goal is structured clinical reporting in electronic healthcare records (EHRs). The Basic Formal Ontology (BFO) is an ontology designed on the basis of types claimed to exist in reality based on a domain-independent ontological theory. Its goal is faithful representation of reality within that theory. The Ontology for General Medical Science (OGMS) extends the BFO by providing definitions for types relevant within the clinical domain. Combining SNOMED CT with the ontological rigor of BFO and OGMS might improve clinical reporting by, f.i., preventing data entry mistakes and inconsistencies, and make EHRs more comparable. To that end, we are developing a logical framework capable of exploiting what SNOMED CT offers terminologically and realism-based ontologies such as the BFO and the OGMS ontologically by means of bridging axioms compatible with the BFO, and expressed in the same CLIF-dialect as used in its axiomatization in first order logic. In this paper, we report on our attempts to detect in the combinations of binary relations that are used in the definition of SNOMED CT's definitions of disorder concepts patterns which might at least partially automate the construction of such axioms. Our findings suggest that this partial automation is indeed possible, but to a smaller extent than we had hoped for. We compare our approach with a recent proposal that seeks to bring SNOMED CT and BFO closer together by reinterpreting SNOMED CT disorders as clinical occurrents. The proposal has its merit in providing a realist underpinning for that part of SNOMED CT's concept model in terms of the BFO, but is not discriminatory enough for an automatic translation into OGMS. Key problem is the lack of face validity of SNOMED CT disorder terms as compared to the formal definitions they are given and this in absence of textual definitions.
{"title":"Axiomatizing SNOMED CT Disorders: Should There Be Room for Interpretation?","authors":"Werner Ceusters, Anuwat Pengput","doi":"10.3233/FAIA231124","DOIUrl":"10.3233/FAIA231124","url":null,"abstract":"<p><p>SNOMED CT is a large <i>concept</i>-based terminology designed according to epistemic, semantic and pragmatic principles relevant to clinicians. Its goal is structured clinical reporting in electronic healthcare records (EHRs). The Basic Formal Ontology (BFO) is an ontology designed on the basis of <i>types</i> claimed to exist in reality based on a domain-independent ontological theory. Its goal is faithful representation of reality within that theory. The Ontology for General Medical Science (OGMS) extends the BFO by providing definitions for types relevant within the clinical domain. Combining SNOMED CT with the ontological rigor of BFO and OGMS might improve clinical reporting by, f.i., preventing data entry mistakes and inconsistencies, and make EHRs more comparable. To that end, we are developing a <i>logical</i> framework capable of exploiting what SNOMED CT offers <i>terminologically</i> and realism-based ontologies such as the BFO and the OGMS <i>ontologically</i> by means of bridging axioms compatible with the BFO, and expressed in the same CLIF-dialect as used in its axiomatization in first order logic. In this paper, we report on our attempts to detect in the combinations of binary relations that are used in the definition of SNOMED CT's definitions of disorder concepts patterns which might at least partially automate the construction of such axioms. Our findings suggest that this partial automation is indeed possible, but to a smaller extent than we had hoped for. We compare our approach with a recent proposal that seeks to bring SNOMED CT and BFO closer together by reinterpreting SNOMED CT disorders as clinical occurrents. The proposal has its merit in providing a realist underpinning for that part of SNOMED CT's concept model in terms of the BFO, but is not discriminatory enough for an automatic translation into OGMS. Key problem is the lack of face validity of SNOMED CT disorder terms as compared to the formal definitions they are given and this in absence of textual definitions.</p>","PeriodicalId":90829,"journal":{"name":"Formal ontology in information systems : proceedings of the ... International Conference. FOIS (Conference)","volume":"377 ","pages":"140-154"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11131161/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141162502","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
D. Allemang, P. Garbacz, Przemysław Grądzki, E. Kendall, R. Trypuz
Collaborative development of a shared or standardized ontology presents unique issues in workflow, version control, testing, and quality control. These challenges are similar to challenges faced in large-scale collaborative software development. We have taken this idea as the basis of a collaborative ontology development platform based on familiar software tools, including Continuous Integration platforms, version control systems, testing platforms, and review workflows. We have implemented these using open-source versions of each of these tools, and packaged them into a full-service collaborative platform for collaborative ontology development. This platform has been used in the development of FIBO, the Financial Industry Business Ontology, an ongoing collaborative effort that has been developing and maintaining a set of ontologies for over a decade. The platform is open-source and is being used in other projects beyond FIBO. We hope to continue this trend and improve the state of practice of collaborative ontology design in many more industries.
{"title":"An Infrastructure for Collaborative Ontology Development","authors":"D. Allemang, P. Garbacz, Przemysław Grądzki, E. Kendall, R. Trypuz","doi":"10.3233/faia210375","DOIUrl":"https://doi.org/10.3233/faia210375","url":null,"abstract":"Collaborative development of a shared or standardized ontology presents unique issues in workflow, version control, testing, and quality control. These challenges are similar to challenges faced in large-scale collaborative software development. We have taken this idea as the basis of a collaborative ontology development platform based on familiar software tools, including Continuous Integration platforms, version control systems, testing platforms, and review workflows. We have implemented these using open-source versions of each of these tools, and packaged them into a full-service collaborative platform for collaborative ontology development. This platform has been used in the development of FIBO, the Financial Industry Business Ontology, an ongoing collaborative effort that has been developing and maintaining a set of ontologies for over a decade. The platform is open-source and is being used in other projects beyond FIBO. We hope to continue this trend and improve the state of practice of collaborative ontology design in many more industries.","PeriodicalId":90829,"journal":{"name":"Formal ontology in information systems : proceedings of the ... International Conference. FOIS (Conference)","volume":"19 1","pages":"112-126"},"PeriodicalIF":0.0,"publicationDate":"2021-12-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78040193","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Ontologies and knowledge bases encode, to a certain extent, the standpoints or perspectives of their creators. As differences and conflicts between standpoints should be expected in multi-agent scenarios, this will pose challenges for shared creation and usage of knowledge sources. Our work pursues the idea that, in some cases, a framework that can handle diverse and possibly conflicting standpoints is more useful and versatile than forcing their unification, and avoids common compromises required for their merge. Moreover, in analogy to the notion of family resemblance concepts, we propose that a collection of standpoints can provide a simpler yet more faithful and nuanced representation of some domains. To this end, we present standpoint logic, a multi-modal framework that is suitable for expressing information with semantically heterogeneous vocabularies, where a standpoint is a partial and acceptable interpretation of the domain. Standpoints can be organised hierarchically and combined, and complex correspondences can be established between them. We provide a formal syntax and semantics, outline the complexity for the propositional case, and explore the representational capacities of the framework in relation to standard techniques in ontology integration, with some examples in the Bio-Ontology domain.
{"title":"Standpoint Logic: Multi-Perspective Knowledge Representation","authors":"Lucía Gómez Álvarez, S. Rudolph","doi":"10.3233/faia210367","DOIUrl":"https://doi.org/10.3233/faia210367","url":null,"abstract":"Ontologies and knowledge bases encode, to a certain extent, the standpoints or perspectives of their creators. As differences and conflicts between standpoints should be expected in multi-agent scenarios, this will pose challenges for shared creation and usage of knowledge sources. Our work pursues the idea that, in some cases, a framework that can handle diverse and possibly conflicting standpoints is more useful and versatile than forcing their unification, and avoids common compromises required for their merge. Moreover, in analogy to the notion of family resemblance concepts, we propose that a collection of standpoints can provide a simpler yet more faithful and nuanced representation of some domains. To this end, we present standpoint logic, a multi-modal framework that is suitable for expressing information with semantically heterogeneous vocabularies, where a standpoint is a partial and acceptable interpretation of the domain. Standpoints can be organised hierarchically and combined, and complex correspondences can be established between them. We provide a formal syntax and semantics, outline the complexity for the propositional case, and explore the representational capacities of the framework in relation to standard techniques in ontology integration, with some examples in the Bio-Ontology domain.","PeriodicalId":90829,"journal":{"name":"Formal ontology in information systems : proceedings of the ... International Conference. FOIS (Conference)","volume":"1 1","pages":"3-17"},"PeriodicalIF":0.0,"publicationDate":"2021-12-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75493381","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The integrated management of industrial systems in future environments like Industry 4.0 requires the effective management of information throughout the engineering life cycle. As systems pass through phases of design, construction, operation, maintenance, renewal or replacement, they will be administered via different information ecosystems, requiring changing perspectives on their descriptive information. A central role in the interplay of software and hardware artefacts, functions, documentation and managing software is played by the descriptions of concepts (i.e. formalised definitions of concepts within the domain of quantification). In this paper we propose a unified formalisation of descriptions that permits consistent analysis of the relationships between the designs, types, products, and concrete artefacts that can be found in the industrial engineering life-cycle. The approach is consistent with our earlier framework that describes artefacts, requirements and functional roles in the context of the DOLCE foundational ontology.
{"title":"Towards Formalisation of Concept Descriptions and Constraints","authors":"Matt Selway, M. Stumptner, W. Mayer","doi":"10.3233/faia210368","DOIUrl":"https://doi.org/10.3233/faia210368","url":null,"abstract":"The integrated management of industrial systems in future environments like Industry 4.0 requires the effective management of information throughout the engineering life cycle. As systems pass through phases of design, construction, operation, maintenance, renewal or replacement, they will be administered via different information ecosystems, requiring changing perspectives on their descriptive information. A central role in the interplay of software and hardware artefacts, functions, documentation and managing software is played by the descriptions of concepts (i.e. formalised definitions of concepts within the domain of quantification). In this paper we propose a unified formalisation of descriptions that permits consistent analysis of the relationships between the designs, types, products, and concrete artefacts that can be found in the industrial engineering life-cycle. The approach is consistent with our earlier framework that describes artefacts, requirements and functional roles in the context of the DOLCE foundational ontology.","PeriodicalId":90829,"journal":{"name":"Formal ontology in information systems : proceedings of the ... International Conference. FOIS (Conference)","volume":"8 1","pages":"18-32"},"PeriodicalIF":0.0,"publicationDate":"2021-12-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84516713","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
A successful application of ontologies relies on representing as much accurate and relevant domain knowledge as possible, while maintaining logical consistency. As the successful implementation of a real-world ontology is likely to contain many concepts and intricate relationships between the concepts, it is necessary to follow a methodology for debugging and refining the ontology. Many ontology debugging approaches have been developed to help the knowledge engineer pinpoint the cause of logical inconsistencies and rectify them in a strategic way. We show that existing debugging approaches can lead to unintuitive results, which may lead the knowledge engineer to opt for deleting potentially crucial and nuanced knowledge. We provide a methodological and design foundation for weakening faulty axioms in a strategic way using defeasible reasoning tools. Our methodology draws from Rodler’s interactive ontology debugging approach and extends this approach by creating a methodology to systematically find conflict resolution recommendations. Importantly, our goal is not to convert a classical ontology to a defeasible ontology. Rather, we use the definition of exceptionality of a concept, which is central to the semantics of defeasible description logics, and the associated algorithm to determine the extent of a concept’s exceptionality (their ranking); then, starting with the statements containing the most general concepts (the least exceptional concepts) weakened versions of the original statements are constructed; this is done until all inconsistencies have been resolved.
{"title":"Debugging Classical Ontologies Using Defeasible Reasoning Tools","authors":"Simone Coetzer, K. Britz","doi":"10.3233/faia210374","DOIUrl":"https://doi.org/10.3233/faia210374","url":null,"abstract":"A successful application of ontologies relies on representing as much accurate and relevant domain knowledge as possible, while maintaining logical consistency. As the successful implementation of a real-world ontology is likely to contain many concepts and intricate relationships between the concepts, it is necessary to follow a methodology for debugging and refining the ontology. Many ontology debugging approaches have been developed to help the knowledge engineer pinpoint the cause of logical inconsistencies and rectify them in a strategic way. We show that existing debugging approaches can lead to unintuitive results, which may lead the knowledge engineer to opt for deleting potentially crucial and nuanced knowledge. We provide a methodological and design foundation for weakening faulty axioms in a strategic way using defeasible reasoning tools. Our methodology draws from Rodler’s interactive ontology debugging approach and extends this approach by creating a methodology to systematically find conflict resolution recommendations. Importantly, our goal is not to convert a classical ontology to a defeasible ontology. Rather, we use the definition of exceptionality of a concept, which is central to the semantics of defeasible description logics, and the associated algorithm to determine the extent of a concept’s exceptionality (their ranking); then, starting with the statements containing the most general concepts (the least exceptional concepts) weakened versions of the original statements are constructed; this is done until all inconsistencies have been resolved.","PeriodicalId":90829,"journal":{"name":"Formal ontology in information systems : proceedings of the ... International Conference. FOIS (Conference)","volume":"29 1","pages":"97-111"},"PeriodicalIF":0.0,"publicationDate":"2021-12-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74287087","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Formal Ontology in Information Systems - Proceedings of the Twelfth International Conference, FOIS 2021, Bozen-Bolzano, Italy, September 11-18, 2021","authors":"B. Bennett, C. Fellbaum","doi":"10.3233/faia344","DOIUrl":"https://doi.org/10.3233/faia344","url":null,"abstract":"","PeriodicalId":90829,"journal":{"name":"Formal ontology in information systems : proceedings of the ... International Conference. FOIS (Conference)","volume":"49 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-12-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85800629","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Fumiaki Toyoshima, A. Barton, Ludger Jansen, J. Éthier
Realizable entities are properties that can be realized in processes of specific correlated types in which the bearer participates. It will be valuable to create a systematic classification of realizable entities because they are useful for various modeling purposes in ontologies. In this paper we outline a unifying framework for realizable entities (including dispositions and roles) in the upper ontology Basic Formal Ontology (BFO) that is theoretically underpinned by J. McKitrick’s pragmatic approach to dispositions. In particular, we develop a formal ontological account of “extrinsic dispositions” and illustrate its potential applications with clarification of functions and roles in BFO.
{"title":"Towards a Unified Dispositional Framework for Realizable Entities","authors":"Fumiaki Toyoshima, A. Barton, Ludger Jansen, J. Éthier","doi":"10.3233/faia210371","DOIUrl":"https://doi.org/10.3233/faia210371","url":null,"abstract":"Realizable entities are properties that can be realized in processes of specific correlated types in which the bearer participates. It will be valuable to create a systematic classification of realizable entities because they are useful for various modeling purposes in ontologies. In this paper we outline a unifying framework for realizable entities (including dispositions and roles) in the upper ontology Basic Formal Ontology (BFO) that is theoretically underpinned by J. McKitrick’s pragmatic approach to dispositions. In particular, we develop a formal ontological account of “extrinsic dispositions” and illustrate its potential applications with clarification of functions and roles in BFO.","PeriodicalId":90829,"journal":{"name":"Formal ontology in information systems : proceedings of the ... International Conference. FOIS (Conference)","volume":"13 1","pages":"64-78"},"PeriodicalIF":0.0,"publicationDate":"2021-12-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74302577","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The primary goal of the General Data Protection Regulation (GDPR) is to regulate the rights and duties of citizens and organizations over personal data protection. Implementing the GDPR is recently gaining much importance for legal reasoning and compliance checking purposes. In this work, we aim to capture the basics of GDPR in a well-founded legal domain modular ontology named OPPD (Ontology for the Protection of Personal Data). Ontology-Driven Conceptual Modeling (ODCM), ontology layering, modularization, and reuse processes are applied. These processes aim to support the ontology engineer in overcoming the complexity of the legal knowledge and developing an ontology model faithful to reality. ODCM is used for grounding OPPD in the Unified Foundational Ontology (UFO). Ontology modularization and layering aim to simplify the ontology building process. Ontology reuse focuses on selecting and reusing Conceptual Ontology Patterns (COPs) from UFO and the legal core ontology UFO-L. OPPD intends to overcome the lack of a representation of legal procedures that most ontologies encountered. The potential use of OPPD is proposed to formalize the GDPR rules by combining ontological reasoning and Logic Programming.
{"title":"Capturing the Basics of the GDPR in a Well-Founded Legal Domain Modular Ontology","authors":"M. E. Ghosh, H. Abdulrab","doi":"10.3233/faia210378","DOIUrl":"https://doi.org/10.3233/faia210378","url":null,"abstract":"The primary goal of the General Data Protection Regulation (GDPR) is to regulate the rights and duties of citizens and organizations over personal data protection. Implementing the GDPR is recently gaining much importance for legal reasoning and compliance checking purposes. In this work, we aim to capture the basics of GDPR in a well-founded legal domain modular ontology named OPPD (Ontology for the Protection of Personal Data). Ontology-Driven Conceptual Modeling (ODCM), ontology layering, modularization, and reuse processes are applied. These processes aim to support the ontology engineer in overcoming the complexity of the legal knowledge and developing an ontology model faithful to reality. ODCM is used for grounding OPPD in the Unified Foundational Ontology (UFO). Ontology modularization and layering aim to simplify the ontology building process. Ontology reuse focuses on selecting and reusing Conceptual Ontology Patterns (COPs) from UFO and the legal core ontology UFO-L. OPPD intends to overcome the lack of a representation of legal procedures that most ontologies encountered. The potential use of OPPD is proposed to formalize the GDPR rules by combining ontological reasoning and Logic Programming.","PeriodicalId":90829,"journal":{"name":"Formal ontology in information systems : proceedings of the ... International Conference. FOIS (Conference)","volume":"50 1","pages":"144-158"},"PeriodicalIF":0.0,"publicationDate":"2021-12-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76804284","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The Winograd Schema Challenge is a general test for Artificial Intelligence, based on problems of pronoun reference resolution. I investigate the semantics and interpretation of Winograd Schemas, concentrating on the original and most famous example. This study suggests that a rich ontology, detailed commonsense knowledge as well as special purpose inference mechanisms are all required to resolve just this one example. The analysis supports the view that a key factor in the interpretation and disambiguation of natural language is the preference for coherence. This preference guides the resolution of co-reference in relation to both explicitly mentioned entities and also implicit entities that are required to form an interpretation of what is being described. I suggest that assumed identity of implicit entities arises from the expectation of coherence and provides a key mechanism that underpins natural language understanding. I also argue that conceptual ontologies can play a decisive role not only in directly determining pronoun references but also in identifying implicit entities and implied relationships that bind together components of a sentence.
{"title":"Semantic Analysis of Winograd Schema No. 1","authors":"B. Bennett","doi":"10.3233/faia210369","DOIUrl":"https://doi.org/10.3233/faia210369","url":null,"abstract":"The Winograd Schema Challenge is a general test for Artificial Intelligence, based on problems of pronoun reference resolution. I investigate the semantics and interpretation of Winograd Schemas, concentrating on the original and most famous example. This study suggests that a rich ontology, detailed commonsense knowledge as well as special purpose inference mechanisms are all required to resolve just this one example. The analysis supports the view that a key factor in the interpretation and disambiguation of natural language is the preference for coherence. This preference guides the resolution of co-reference in relation to both explicitly mentioned entities and also implicit entities that are required to form an interpretation of what is being described. I suggest that assumed identity of implicit entities arises from the expectation of coherence and provides a key mechanism that underpins natural language understanding. I also argue that conceptual ontologies can play a decisive role not only in directly determining pronoun references but also in identifying implicit entities and implied relationships that bind together components of a sentence.","PeriodicalId":90829,"journal":{"name":"Formal ontology in information systems : proceedings of the ... International Conference. FOIS (Conference)","volume":"559 1","pages":"33-47"},"PeriodicalIF":0.0,"publicationDate":"2021-12-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78901774","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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