1. The Knowledge Acquisition Bottleneck Revisited: How can we build large KBs?
Illustrations of different approaches
Peter Clark and John Thompson
Boeing Research
2004

2. Premise Intelligent machines needs lots of knowledge, for
question-answering
intelligent search
information integration
natural language understanding
decision support
modeling
etc. etc.
Much of this knowledge can be drawn from some general repository of reusable knowledge
e.g., WordNet
How does one build such a repository?
“No-one considers hand-building a large KB to be a realistic proposition these days” [paraphrase of Daphne Koller, 2004]

3. 1. Build it by Hand “Let’s roll up our sleeves and get on with it!”
But: It’s a daunting task
Our own work
Cyc
+ Lots in it, (Relatively) well designed ontology
- 650 person-years effort so far
- Still patchy coverage (why?)
Difficult to use outside Cycorp

4. 1. Build it by Hand (cont) WordNet + Easy to use + Comprehensive
Little inference-supporting knowledge in
Ad hoc ontology

5. 1. Build it by Hand (cont) The Component Library
Claim: can bound the required knowledge by working at a coarse-grained level
+ Large, more doable
Hard to use, still very incomplete

6. 2. Extract from Dictionaries
- MindNet
+ Automatically built
Unusable?
Extended WordNet
+ Won TREC competition
- Still somewhat incoherent
Lot of manual labor

7. 3. Corpus-based Text/Web Mining
- Schubert’s system
+ Automatic
+ Lots of knowledge
Noisy
No word senses
Only grabs certain kinds of knowledge
30M entries…

8. 3. Corpus-based Text/Web Mining (cont)
- KnowIt (Etsioni)
+ automatic
only factoids

9. 4. Community-Based Acquisition
Knowledge entry by the masses
OpenMind
+ Large
Full of junk, unusable (?)
Would this work with better acquisition tools?
(see next slide for illustration)

11. 5. Use Existing Resources
e.g.,
databases
CIA World Fact Book
Web data/services
e.g., SRI/ISI’s ARDA QA system
+ Syntactically simple
+ Available
Largely limited to factoids
Information integration is a major challenge
different ontologies, contradictory data

12. Where to? Can we bound the knowledge needed
for a particular application
for a useful, sharable, general resource?
Which of these approaches seems most realistic?
build by hand
extract from dictionaries
mine text corpora
community knowledge entry
use existing resources