AKBC 2013

Automated Knowledge Base Construction (AKBC) 2013: The 3rd Workshop on Knowledge Extraction at CIKM 2013 in San Francisco, October 27-28, 2013.

Supported in part by

The advances in information extraction, machine learning, and natural language processing have led to the creation of large knowledge bases (KBs) from Web sources. Notable endeavors in this direction include Wikipedia-based approaches (such as YAGO, DBpedia, and Freebase), systems that extract from the entire Web (such as NELL and PROSPERA) or from speci c domains (such as Rexa), and open information extraction approaches (TextRunner, PRISMATIC). This trend has led to new applications that make use of semantics. Most prominently, all major search engine providers (Yahoo!, Microsoft Bing, and Google) nowadays experiment with semantic tools. The Semantic Web, too, benefits from the new approaches.

With this year’s workshop, we would like to resume the positive experiences from two previous workshops: AKBC-2010 and AKBC-WEKEX-2012. The AKBC-2013 workshop will serve as a forum for researchers working in the area of automated knowledge harvesting from text. By having invited talks by leading researchers from industry, academia, and the government, and by focusing particularly on vision papers, we aim to provide a vivid forum of discussion about the field of automated knowledge base construction.

Day 1: Sunday, October 27th, 2013

Start End Speaker Title
9:00 9:15 - Poster Setup
9:15 9:45 Fabian Suchanek (MPI) Welcome Message (slides)
9:45 10:30 Chris Manning (Stanford) Texts are Knowledge (slides)
10:30 11:00 Break
11:00 11:45 Bonnie Dorr (DARPA) HLT Programs at DARPA: Challenges, Solutions, and Applications
11:45 12:30 Evgeniy Gabrilovich (Google) Knowledge Vault: A Web-Scale Approach to Probabilistic Knowledge Fusion
Recent years have witnessed a proliferation of large-scale knowledge bases, including Wikipedia, Freebase, YAGO, Microsoft's Satori, and Google's Knowledge Graph. To increase the scale even further, we need to use automatic methods for knowledge base construction. Previous approaches have primarily focused on text-based extraction, which can be very noisy. In this talk, we will introduce Knowledge Vault, a Web-scale probabilistic knowledge base that combines text-based extractions with prior knowledge, derived from existing knowledge repositories. We employ supervised machine learning methods for fusing these distinct information sources. The Knowledge Vault is substantially bigger than any previously published structured knowledge repository, and features a probabilistic inference system that computes calibrated probabilities of fact correctness. In the second part of the talk, we will discuss the frontiers of research in knowledge discovery on the Web.
12:30 1:30 Lunch Break
1:30 1:40 Sameer Singh Joint Inference of Entities, Relations and Coreference
1:40 1:50 Xiao Ling Extracting Meronyms for a Biology Knowledge Base Using Distant Supervision
1:50 2:00 Michael Wick Assessing Confidence of Knowledge Base Content with an Experimental Study in Entity Resolution
2:00 2:10 Jay Pujara Ontology-Aware Partitioning for Knowledge Graph Identification
2:10 2:20 Jonathan Gordon Reporting Bias and Knowledge Extraction
2:20 2:30 Bhavana Dalvi Classifying Entities into an Incomplete Ontology
2:30 2:40 Peter Clark A Study of the AKBC Requirements for Passing an Elementary Science Test
2:40 2:50 Luis Galárraga Mining Rules to Align Knowledge Bases
2:50 3:00 Thomas Huet Mining History with Le Monde
3:00 3:30 Break
3:30 5:00 Poster Session

Day 2: Monday, October 28th, 2013

Start End Speaker Title
9:00 9:45 Andrew McCallum (UMass) TBA
9:45 10:00 Dan Weld (UWashington) Distant Supervision for Relation Extraction: Progress & Problems
10:30 11:00 Break
11:00 11:45 Tom Mitchell (CMU) NELL: Three new directions
11:45 12:30 James Mayfield (JHU) TBA
12:30 1:30 Lunch Break
1:30 2:15 Alon Halevy (Google) Biperpedia: An ontology for search applications
2:15 3:00 Haixun Wang (Google) TBA
3:00 3:30 Break
3:30 5:00 Unconference Session

Talk & Poster

  • Paper 01:
    Sameer Singh, Sebastian Riedel, Brian Martin, Jiaping Zheng, Andrew McCallum
    Joint Inference of Entities, Relations, and Coreference
    (Discussion, Paper)
  • Paper 02:
    Xiao Ling, Daniel S Weld
    Extracting Meronyms for a Biology Knowledge Base Using Distant Supervision
  • Paper 03:
    Michael Wick, Sameer Singh, Ari Kobren, Andrew McCallum
    Assessing Confidence of Knowledge Base Content with an Experimental Study in Entity Resolution
    (Discussion, Paper)
  • Paper 04:
    Jay Pujara, Hui Miao, Lise Getoor, William Cohen
    Ontology-Aware Partitioning for Knowledge Graph Identification
    (Discussion, Paper)
  • Paper 05:
    Jonathan Gordon, Benjamin Van Durme
    Reporting Bias and Knowledge Extraction
    (Discussion, Paper)
  • Paper 06:
    Bhavana Dalvi, William W Cohen, Jamie Callan
    Classifying Entities into an Incomplete Ontology
    (Discussion, Paper)
  • Paper 07:
    Peter Clark, Phil Harrison, Niranjan Balasubramanian
    A Study of the AKBC Requirements for Passing an Elementary Science Test
    (Discussion, Paper)
  • Paper 08:
    Luis Galárraga, Nicoleta Preda, Fabian Martin Suchanek
    Mining Rules to Align Knowledge Bases
    (Discussion, Paper)
  • Paper 09:
    Thomas HUET, Joanna Biega, Fabian M. Suchanek
    Mining History with Le Monde


  • 10: Jeffrey Dalton, Laura Dietz. Constructing Query-Specific Knowledge Bases (Discussion, Paper)
  • 11: Doug Downey, Chandra Sekhar Bhagavatula. Using Natural Language to Integrate, Evaluate, and Optimize Extracted Knowledge Bases (Discussion, Paper)
  • 12: Michael Wick, Sameer Singh, Harshal Pandya, Andrew McCallum. A Joint Model for Discovering and Linking Entities (Discussion, Paper)
  • 13: Benjamin Roth, Tassilo Barth, Michael Wiegand, Dietrich Klakow. A Survey of Noise Reduction Methods for Distant Supervision (Discussion)
  • 14: Limin Yao, Sebastian Riedel, Andrew McCallum. Universal Schema for Entity Type Prediction (Discussion)
  • 15: Maryam Siahbani, Ravikiran Vadlapudi, Max Whitney, Anoop Sarkar. Knowledge Base Population and Visualization Using an Ontology based on Semantic Roles (Discussion, Paper)
  • 16: Michael Schuhmacher, Simone Paolo Ponzetto. Exploiting DBPedia for Web search results clustering (Discussion)
  • 17: Xinyu Li, Roya Rastan, John Shepherd, Hye-Young Paik. Automatic Affiliation Extraction from Calls-For-Papers (Discussion)
  • 18: Eric Yeh, John Niekrasz, Dayne Freitag. Unsupervised Discovery and Extraction of Semi-structured Regions in Text via Self-Information (Discussion)
  • 19: Priya Radhakrishnan, Vasudeva Varma. Extracting Semantic Knowledge from Wikipedia Category Names (Discussion)

Camera Ready Instructions

    Camera ready deadline for all accepted papers (i.e., irrespective of presentation mode) is August 25, 2013. Camera ready preparation instructions are available here. All papers should be formatted as maximum 4 pages of content + references, with total upper limit of 6 pages. Submissions links will be mailed out to the authors shortly.

All accepted papers should be presented by at least one author. Every paper should be presented a poster. The poster dimensions are as specified here.

In addition, the papers listed under "Talk & posters" should be presented by a short talk. We allocate 10 minutes per talk, which includes speaker change, the talk itself, and one or two quick questions. Please see above for the schedule of the talks. The slides for the talk should be emailed to info@akbc.ws by 9am Pacific on October 27, 2013. We shall use a single comuter (Mac) to save time during talk transition. Please name your file XX_YYY.ZZZ, where XX is the two-digit decimal number of your talk slot (01, 02, ...), YYY is your name, and ZZZ is any of the supported file formats (PPT, PPTX, PDF, SVG, Keynote).

For any questions, please mail info@akbc.ws
  • Doug Downey (Northwestern University)
  • Matt Gardner (Carnegie Mellon University)
  • Rainer Gemulla (Max-Planck Institute for Informatics)
  • Estevam Hruschka (Federal University of Sao Carlos)
  • Jayant Krishnamurthy (Carnegie Mellon University)
  • Zornitsa Kozareva (University of Southern California)
  • Sebastian Michel (Max-Planck Institute for Informatics)
  • Bhavana Dalvi Mishra (Carnegie Mellon University)
  • Marius Pasca (Google Research)
  • Alan Ritter (University of Washington)
  • Ralf Schenkel (Max-Planck Institute for Informatics)
  • Gerhard Weikum (Max-Planck Institute for Informatics)
  • Michael Wick (University of Massachusetts, Amherst)
  • Derry Wijaya (Carnegie Mellon University)
  • Limin Yao (University of Massachusetts, Amherst)