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Joint Reasoning for Multi-Faceted Commonsense Knowledge [article]

Yohan Chalier, Simon Razniewski, Gerhard Weikum
2020 arXiv   pre-print
This paper aims to overcome these limitations by introducing a multi-faceted model of CSK statements and methods for joint reasoning over sets of inter-related statements.  ...  Commonsense knowledge (CSK) supports a variety of AI applications, from visual understanding to chatbots.  ...  D achieves high precision for its multi-faceted output. e resulting commonsense knowledge bases contain more than 1.6m statements about 74k concepts, and will be made publicly available.  ... 
arXiv:2001.04170v2 fatcat:wlih2w4wl5cr5okfimh7l5zwoe

Dice: A Joint Reasoning Framework for Multi-Faceted Commonsense Knowledge

Yohan Chalier, Simon Razniewski, Gerhard Weikum
2020 International Semantic Web Conference  
We present a web prototype for the Dice framework for joint consolidation of noisy multi-faceted commonsense knowledge (CSK) [1] .  ...  In the demonstration session, participants will be familiarized with the multi-faceted knowledge representation formalism used in Dice, and get the opportunity to inspect grounded constraint systems and  ...  Dice overcomes these limitations by introducing a multi-faceted model of CSK statements and methods for joint reasoning over sets of inter-related statements [1] .  ... 
dblp:conf/semweb/ChalierRW20 fatcat:6foabhr4ireqxb5fgutc6uj3ky

Structured Self-Supervised Pretraining for Commonsense Knowledge Graph Completion

Jiayuan Huang, Yangkai Du, Shuting Tao, Kun Xu, Pengtao Xie
2021 Transactions of the Association for Computational Linguistics  
To develop commonsense-grounded NLP applications, a comprehensive and accurate commonsense knowledge graph (CKG) is needed.  ...  The reason is that our methods can capture long-range relationships among concepts and multi-faceted semantics of concepts.  ...  Graph-to-path pretraining integrates the merits of router pretraining and long-path pretraining, which is good for tasks involving both long-range and multi-faceted reasoning, such as text generation from  ... 
doi:10.1162/tacl_a_00426 fatcat:gr7wj3qplzax5bdccavh7cikvm

Commonsense Knowledge Base Construction in the Age of Big Data [article]

Simon Razniewski
2021 arXiv   pre-print
In this demonstration we will showcase three systems for automated commonsense knowledge base construction, highlighting each time one aspect of specific interest to the data management community.  ...  (i) We use Quasimodo to illustrate knowledge extraction systems engineering, (ii) Dice to illustrate the role that schema constraints play in cleaning fuzzy commonsense knowledge, and (iii) Ascent to illustrate  ...  Motivation Knowledge and reasoning about general-world concepts are major challenges in AI.  ... 
arXiv:2105.01925v1 fatcat:v45fcf5hrbbl7fmnvx72ddnhea

Joint Constrained Learning for Event-Event Relation Extraction [article]

Haoyu Wang, Muhao Chen, Hongming Zhang, Dan Roth
2021 arXiv   pre-print
Due to the lack of jointly labeled data for these relational phenomena and the restriction on the structures they articulate, we propose a joint constrained learning framework for modeling event-event  ...  We show that our joint constrained learning approach effectively compensates for the lack of jointly labeled data, and outperforms SOTA methods on benchmarks for both temporal relation extraction and event  ...  Acknowledgement We appreciate the anonymous reviewers for their insightful comments.  ... 
arXiv:2010.06727v2 fatcat:lrruts6vhvewlab5yxupltit6q

MINING CAUSALITY FROM IMPERFECT DATA

LAWRENCE J. MAZLACK
2004 Applied Computational Intelligence  
A common sense understanding of the world tells us that we have to deal with imprecision, uncertainty and imperfect knowledge.  ...  A difficulty is striking a good balance between precise formalism and commonsense imprecise reality. An algorithmic method of accommodating imprecision in causality is needed.  ...  In a way, the term "causality" is like "truth" --a word with many meanings and facets. Some definitions are extremely precise but often unusable for commonsense reasoning.  ... 
doi:10.1142/9789812702661_0031 fatcat:qwzcc4yvkzgh7g7rizkrzlnl5i

Beyond Language: Learning Commonsense from Images for Reasoning [article]

Wanqing Cui, Yanyan Lan, Liang Pang, Jiafeng Guo, Xueqi Cheng
2020 arXiv   pre-print
This paper proposes a novel approach to learn commonsense from images, instead of limited raw texts or costly constructed knowledge bases, for the commonsense reasoning problem in NLP.  ...  We also give some case studies to show what knowledge is learned from images and explain how the generated scene layout helps the commonsense reasoning process.  ...  Chalier et al. (2020) proposes a multi-faceted model of commonsense knowledge statements to capture more expressive meta-properties.  ... 
arXiv:2010.05001v1 fatcat:7mmd4azoxnebrnm7umhiwibsji

Reasoning with Heterogeneous Knowledge for Commonsense Machine Comprehension

Hongyu Lin, Le Sun, Xianpei Han
2017 Proceedings of the 2017 Conference on Empirical Methods in Natural Language Processing  
In this paper, we propose a multi-knowledge reasoning method, which can exploit heterogeneous knowledge for commonsense machine comprehension.  ...  Reasoning with commonsense knowledge is critical for natural language understanding.  ...  Moreover, we sincerely thank the reviewers for their valuable comments.  ... 
doi:10.18653/v1/d17-1216 dblp:conf/emnlp/LinSH17 fatcat:22cujx67tfcfvpnsmkepyms36q

A Semantic Framework to Enrich Collaborative Tables with Domain Knowledge

Anna Goy, Diego Magro, Giovanna Petrone, Marco Rovera, Marino Segnan
2015 Proceedings of the 7th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management  
We tested this approach on the geographic domain, by connecting resources to commonsense geographic knowledge and to information available in GeoNames.  ...  In this paper we present a project aimed at enhancing a collaborative environment for resource management (SemT++) with domain knowledge, represented by a local ontology and a connection to external data  ...  folksonomies, i.e., multi-facets classifications collaboratively and incrementally built by users in a bottom-up perspective .  ... 
doi:10.5220/0005586103710381 dblp:conf/ic3k/GoyMPRS15 fatcat:cutmwinhfzhcjomqgjvejmuwq4

Semi-supervised learning for big social data analysis

Amir Hussain, Erik Cambria
2018 Neurocomputing  
The latter is developed by merging a graph representation of commonsense with a linguistic resource for the lexical representation of affect.  ...  on a knowledge base.  ...  The key to performing commonsense reasoning is to find a good trade-off for knowledge representation.  ... 
doi:10.1016/j.neucom.2017.10.010 fatcat:ggjos3kyzvhijkykoncnqwgkse

Explaining Question Answering Models through Text Generation [article]

Veronica Latcinnik, Jonathan Berant
2020 arXiv   pre-print
Large pre-trained language models (LMs) have been shown to perform surprisingly well when fine-tuned on tasks that require commonsense and world knowledge.  ...  In this work, we propose a model for multi-choice question answering, where a LM-based generator generates a textual hypothesis that is later used by a classifier to answer the question.  ...  Acknowledgements We thank Inbar Oren and Guy Tevet for their useful suggestions.  ... 
arXiv:2004.05569v1 fatcat:alud5gmvzba3rjzsc65upxej6a

TVShowGuess: Character Comprehension in Stories as Speaker Guessing [article]

Yisi Sang, Xiangyang Mou, Mo Yu, Shunyu Yao, Jing Li, Jeffrey Stanton
2022 arXiv   pre-print
We propose a new task for assessing machines' skills of understanding fictional characters in narrative stories.  ...  We restrict this category to be the aforementioned commonsense knowledge types, to distinguish from other relatively under-studied commonsense knowledge, such as the commonsense of dialogue flow required  ...  They usually cover a single facet of a multi-dimensional persona (Moore et al., 2017) , e.g., personal facts (Zhang et al., 2018) or personality types (Mairesse and Walker, 2007; .  ... 
arXiv:2204.07721v1 fatcat:7dpatke53jfizhmlgp63vrrkjm

Multimodal Research in Vision and Language: A Review of Current and Emerging Trends [article]

Shagun Uppal, Sarthak Bhagat, Devamanyu Hazarika, Navonil Majumdar, Soujanya Poria, Roger Zimmermann, Amir Zadeh
2020 arXiv   pre-print
Moreover, we shed some light on multi-disciplinary patterns and insights that have emerged in the recent past, directing this field towards more modular and transparent intelligent systems.  ...  Visual Commonsense Reasoning (VCR): Visual Commonsense Reasoning is the task of inferring cognitive understanding and commonsense information by a machine on seeing an image.  ...  Visual Commonsense Reasoning (VCR) The task of VCR [128] was introduced to develop higherorder cognition in vision systems and commonsense reasoning of the world so that they can provide justifications  ... 
arXiv:2010.09522v2 fatcat:l4npstkoqndhzn6hznr7eeys4u

Product review summarization from a deeper perspective

Duy Khang Ly, Kazunari Sugiyama, Ziheng Lin, Min-Yen Kan
2011 Proceeding of the 11th annual international ACM/IEEE joint conference on Digital libraries - JCDL '11  
Importantly, our system not only extracts the review sentiments but also the underlying justification for their opinion.  ...  With product reviews growing in depth and becoming more numerous, it is growing challenge to acquire a comprehensive understanding of their contents, for both customers and product manufacturers.  ...  To address this, we propose to generate the summary in Figure 1 (b) which further provides a representative reason for the sentiment and clusters other, similar reasons to remove redundancy.  ... 
doi:10.1145/1998076.1998134 dblp:conf/jcdl/LySLK11 fatcat:jltlorahfngwppjexecgxng6s4

INFOTABS: Inference on Tables as Semi-structured Data [article]

Vivek Gupta, Maitrey Mehta, Pegah Nokhiz, Vivek Srikumar
2020 arXiv   pre-print
Our analysis shows that the semi-structured, multi-domain and heterogeneous nature of the premises admits complex, multi-faceted reasoning.  ...  We argue that such data can prove as a testing ground for understanding how we reason about information.  ...  Acknowledgements We thank members of the Utah NLP group for their valuable insights and suggestions at various stages of the project; and reviewers their helpful comments.  ... 
arXiv:2005.06117v1 fatcat:p763rr45kbdurh3xtxjygm5rbu
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