Knowledge Bases

Block seminar, 7 ECTS credits, winter semester 2017–18

Basic Information

  • Type: Block seminar
  • Lecturer: Simon RazniewskiParamita Mirza
  • Credits: 7 ECTS credits
  • Registration: Course is full, unfortunately no further registrations can be accepted
  • Dates: November 16 & 23, 2017 (introductory meetings) and March 6 & 7, 2018 (block seminar).

The seminar is a block seminar and will take place on two (consecutive) days at the end of February or beginning of March--the exact days to be agreed with the participants. There will also be two meetings at the beginning of the semester, for which participation is mandatory.


  • November 16, 2017 -- Slides for the kick-off meeting are available [pdf]
  • November 16, 2017 -- Please fill in the Doodle for the block seminar days
  • November 20, 2017 -- Template for seminar paper available [zip]
  • November 22, 2017 -- Based on the Doodle, the block seminar dates have been fixed to March 6 and 7
  • November 23, 2017 -- Slides from the second meeting are online [pdf]
  • December 6, 2017 -- Tentative block seminar schedule is online (see below)


A detailed list is below

Representation, collection and extraction of general knowledge in knowledge bases (KBs) is at the core of many AI applications. In this seminar, we cover a range of topics around KBs, in particular factual KBs (e.g., Wikidata, YAGO, DBPedia), common-sense KBs (e.g., science knowledge, howto-knowledge, script knowledge) and non-textual KBs (e.g., ImageNet). We explore how these KBs are constructed and how they are used in various applications such as question answering (QA), story/script prediction and biography generation. We also explore learning new facts over KBs.


  • October 4, 2017 -- Registration deadline
  • November 16, 2017 -- Kick-off meeting (participation is mandatory) [pdf]
    • Time: 11:30 am - 13:00 am
    • Place: Room 23, MPI-Inf building (E 1.4, ground level)
      • Explanation of the structure and organization of the seminar
      • Brief introduction to knowledge bases
      • Presentation of the topics
  • November 23, 2017 -- "How to prepare and present a seminar talk" (participation is mandatory)
    • Time: 11:30 am - 13:00 am
    • Place: Room 23, MPI-Inf building (E 1.4, ground level)
      • As this is a block seminar, it is particularly crucial that the students' presentations are of high quality. This lecture aims at preparing the participants in such a way that their slides and presentations will be of high quality.
      • Topic assignment: students prepare a preferred ranked list of proposed topics, we will do the live assignment based on a randomly decided order.
  • December 13, 2017, 23:59 -- students send a suggestion of the outline of their seminar paper, including an itemization of the planned content for each section.
  • January 31, 2018, 23:59 -- students submit their final seminar paper.
  • February 20, 2018, 23:59 -- students send preliminary slides
  • March 3, 2018, 23:59 -- students send their final slides which they will use in the block seminar
  • March 6, 2018 -- Block seminar, Day 1 - Room 433, MPI-Inf building (E 1.4, 4th floor)
  • March 7, 2018 -- Block seminar, Day 2 - Room 433, MPI-Inf building (E 1.4, 4th floor)

Tentative Seminar Schedule

Format: 25 minutes presentation, 10 minutes discussion

March 6:
 10:00-10:35 1: Collaborative KBs: Wikidata (Safura Isayeva)
 10:35-11:10 2: Structured information extraction: DBpedia and YAGO (Mang Zhao)
   10 minutes break
 11:20-11:55 3: KB population in the TAC 2016 challenge (Nitisha Jain)
 11:55-12:30 4: General common-sense KBs: ConceptNet and WebChild (Xueting Li)
   1 hour lunch break
 13:30-14:05 5: Domain-specific activity KBs (Anu Goel)
 14:05-14:40 6: The Allen AI science challenge & building a science KB: Aristo (Frederick Schmitt)
   10 minutes break
 14:50-15:25 7: KB association rule mining (Joscha Cüppers)

March 7:
 10:00-10:35 8: Enriching KBs with named events: EVIN (Harshita Jhavar)
 10:35-11:10 9: Exploring and profiling KBs (Adrian Spirescu)
   10 minutes break
 11:20-11:55 10: KB question answering (Shrestha Ghosh)
 11:55-12:30 11: Hybrid question answering using KBs and text (Aydan Rende)
   1 hour lunch break
 13:30-14:05 12: Non-encyclopedic QA in the science domain (Khansa Rekik)
 14:05-14:40 13: Biography generation (David Neisens)
   5 minutes break
 14:45-15:00 Closing remarks

Rules and Grading

  • Participation in the kick-off meeting, the "How to prepare and present a seminar talk" lecture, and both days of the block seminar is mandatory.
  • Students will be assigned a particular topic and have to submit a seminar paper (template will be provided) and give a presentation (25 minutes + 10 minutes for discussion) over the topic.
  • Grading will be based on:
    • the report
    • the presentation
    • knowledge on the subject (as evidenced in the discussion after the presentation)
    • activity in the discussions
    • ability to stick to deadlines
  • Attention: According to the study regulations, you are only allowed to withdraw from the seminar within three weeks after the kick-off meeting, i.e., until December 7. Later withdrawal counts as "failed".


Area I: Knowledge Bases

  • 1: Collaborative KBs: Wikidata -- Safura Isayeva (Simon)
    • Wikidata: a free collaborative knowledge base (Vrandečić & Krötzsch, CACM 2014) [pdf]
    • Introducing Wikidata to the linked data web (Erxleben et al., ISWC 2014) [pdf]
  • 2: Structured information extraction: DBpedia and YAGO -- Mang Zhao (Simon)
    • DBpedia – A large-scale, multilingual knowledge base extracted from Wikipedia (Lehmann, et al., Semantic Web 2015) [pdf]
    • YAGO2: A spatially and temporally enhanced knowledge base from Wikipedia (Hoffart et al., Artificial Intelligence 2013) [pdf]
  • 3: KB population in the TAC 2016 challenge -- Nitisha Jain (Paramita)
    • TAC Challenge [link]
  • 4: General common-sense KB: ConceptNet and WebChild -- Xueting Li (Paramita)
    • Representing general relational knowledge in ConceptNet 5 (Speer & Harvasi, LREC 2012) [pdf]
    • WebChild: Harvesting and Organizing Commonsense Knowledge from the Web (Tandon et al., WSDM 2014) [pdf]
  • 5: Domain-specific activity KBs -- Anu Goel (Paramita)
    • HowTo KB -- Distilling task knowledge from How-To communities (Chu et al., WWW 2017) [pdf]
    • A hierarchical bayesian model for unsupervised induction of script knowledge (Frermann et al., EACL 2014) [pdf]
  • 6: The Allen AI science challenge & building a science KB: Aristo -- Frederik Schmitt (Paramita)
    • Domain-targeted, high precision knowledge extraction (Mishra et al., TACL 2017) [pdf]
    • Moving beyond the Turing test with the Allen AI Science Challenge (Schoenick et al., CACM 2016) [pdf]

Area II: Learning over Knowledge Bases

  • 7: KB association rule mining -- Joscha Cüppers (Simon)
    • Fast rule mining in ontological knowledge bases with AMIE+ (Galárraga et al., VLDB 2015) [pdf]
  • 8: Enriching KBs with Named Events: EVIN -- Harshita Jhavar (Paramita)
    • A Fresh Look on Knowledge Bases: Distilling Named Events from News (Kuzey et al., CIKM 2014) [pdf]

Area III: Using Knowledge Bases

  • 9: Exploring and profiling KBs -- Adrian Spirescu (Simon)
    • Wikidata SQID browser [link]
    • Faceted search over RDF-based knowledge graphs (Arenas et al., JWS 2016) [pdf]
    • Loupe - An Online Tool for Inspecting Datasets in the Linked Data Cloud (Mihindukulasooriya et al., ISWC 2015) [pdf]
  • 10: KB question answering -- Shrestha Ghosh (Simon)
    • Automated template generation for question answering over knowledge graphs (Abujabal et al., WWW 2017) [pdf]
    • Robust question answering over the web of linked data (Yahya et al., CIKM 2013) [pdf]
  • 11: Hybrid question answering using KBs and text -- Aydan Rende (Paramita)
    • Question answering on Freebase via relation extraction and textual evidence (Xu et al., ACL 2016) [pdf]
    • Open question answering over curated and extracted knowledge bases (Fader et al., KDD 2014) [pdf]
  • 12: Non-encyclopedic QA in the science domain (continuation of Topic 5) -- Khansa Rekik (Simon)
    • Answering complex questions using open information extraction (Khot et al., ACL 2017) [pdf]
  • 13: Biography generation - David Neisens (Simon)
    • Learning to generate one-sentence biographies from Wikidata (Chisholm et al., EACL 2017 [pdf]