Open Mind Common Sense: Knowledge Acquisition from the General Public

Open Mind Common Sense is a knowledge acquisition system designed to acquire commonsense knowledge from the general public over the web. We describe and evaluate our first fielded system, which enabled the construction of a 450,000 assertion commonsense knowledge base. We then discuss how our second-generation system addresses weaknesses discovered in the first. The new system acquires facts, descriptions, and stories by allowing participants to construct and fill in natural language templates. It employs word-sense disambiguation and methods of clarifying entered knowledge, analogical inference to provide feedback, and allows participants to validate knowledge and in turn each other.

[1]  Ernest Davis,et al.  Representations of commonsense knowledge , 2014, notThenot Morgan Kaufmann series in representation and reasoning.

[2]  Erik T. Mueller.  A database and lexicon of scripts for ThoughtTreasure , 2000, ArXiv.

[3]  David G. Stork,et al.  Building intelligent systems one e-citizen at a time , 1999, IEEE Intell. Syst..

[4]  R. Bareiss,et al.  Supporting Start-to-Finish Development of Knowledge Bases , 2005, Machine Learning.

[5]  Gary C. Borchardt,et al.  Understanding Causal Descriptions of Physical Systems , 1992, AAAI.

[6]  Yolanda Gil,et al.  Designing Scripts to Guide Users in Modifying Knowledge-based Systems , 1999, AAAI/IAAI.

[7]  Henry Lieberman,et al.  GOOSE: A Goal-Oriented Search Engine with Commonsense , 2002, AH.

[8]  Yolanda Gil,et al.  Knowledge Refinement in a Reflective Architecture , 1994, AAAI.

[9]  Rada Mihalcea,et al.  Building a Sense Tagged Corpus with Open Mind Word Expert , 2002, SENSEVAL.

[10]  Yolanda Gil,et al.  An integrated environment for knowledge acquisition , 2001, IUI '01.

[11]  Norbert E. Fuchs,et al.  Attempto Controlled English (ACE) , 1996, ArXiv.

[12]  M. Shanahan.  Solving the frame problem , 1997 .

[13]  Push Singh,et al.  The Public Acquisition of Commonsense Knowledge , 2002 .

[14]  Claire Cardie,et al.  Empirical Methods in Information Extraction , 1997, AI Mag..

[15]  Henry Lieberman,et al.  Watch what I do: programming by demonstration , 1993 .

[16]  Henry Lieberman,et al.  Adaptive Linking between Text and Photos Using Common Sense Reasoning , 2002, AH.

[17]  David G. Stork.  Toward a Computational Theory of Data Acquisition and Truthing , 2001, COLT/EuroCOLT.

[18]  Erik T. Mueller.  A calendar with common sense , 2000, IUI '00.

[19]  Ramanathan V. Guha,et al.  Enabling agents to work together , 1994, CACM.

[20]  Douglas B. Lenat,et al.  CYC: a large-scale investment in knowledge infrastructure , 1995, CACM.

[21]  Jim Blythe,et al.  Knowledge Acquisition using an English-Based Method Editor , 1999 .