Difference between revisions of "Vulcan/MeetingNotes/Aug09 2013"
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<b>3. What happens when deductive inference fails? </b> | <b>3. What happens when deductive inference fails? </b> | ||
− | <i>Approach A:</i> | + | <i>Approach A:</i> Identify axioms (tuples) that are highly "similar" to some node in the backward chained derivation graph. |
− | Identify axioms (tuples) that are highly "similar" to some node in the backward chained derivation graph. | ||
Add weak entailment rules (axiom -> derivation node) scored using edit distance. | Add weak entailment rules (axiom -> derivation node) scored using edit distance. | ||
− | <i>Approach B:</i> | + | <i>Approach B:</i> Find the most plausible answer. |
− | Find the | ||
<blockquote> | <blockquote> |
Revision as of 23:10, 9 August 2013
Update
- Focusing on system development.
- 1. Inferencer stub using Jena. Stub takes in axioms and rules and outputs a derviation.
- Jena API doesn't readily support multiple derivations.
- Ask Jena community to find out if this is possible or
replace with OWLIM (or Seasame) triplestore/inference systems.
- 2. Tested stub with axioms and rules that would help us solve the iron nail example.
- 3. Built Proposition extractor stub that converts the answer assertions into propositions represented as Open IE 4.0 tuples
- Resource collection
- 1. Gathered assertions from Peter/Phil. Each assertion corresponds to a single multiple choice answer.
- 2. Found RDF representations for WordNet and imported them into Jena.
- Analysis
- 1. Selected 10 propositions that are single Open IE tuples as starting targets.
- 2. Started to write down steps involved in verifying these propositions.
Notes
1. Do we really needed an inference engine (Jena)?
We need a way to scale down the search space for BLP and MLN. Inference engine is one way to do this.
2. Discussed the inference steps involved for 5 different questions.
It was clear we may not be able to have a complete derivation always.
3. What happens when deductive inference fails?
Approach A: Identify axioms (tuples) that are highly "similar" to some node in the backward chained derivation graph. Add weak entailment rules (axiom -> derivation node) scored using edit distance.
Approach B: Find the most plausible answer.
Example 1: (x, helps, a fox find food), where x is one of {sense of smell, thick fur, long tail, pointed teeth}
We don't find sentences that directly state that "sense of smell helps fox find food".
However, several sentences say "sense of smell helps animals find food":"smell helps * find food" returns 7 million hits on Google.
"fur helps * find food" returns no hits.From this we cannot prove that foxes use sense of smell to find food but it increases our belief in it.
Example 2: (x, conductor of, electricity), where x is one of {iron nail, rubber boat, wax crayon, plastic cup}
We don't find sentences that directly state that "iron nail is a conductor of electricity" (or that it conducts electricity).
However, several sentences match the pattern "iron * is a conductor of electricity":"iron * is a conductor of electricity" returns 794,000 hits on Google.
"rubber * is a conductor of electricity" returns 196,000 hits.
This is a form of abductive reasoning using linguistically motivated templates.
4. How to use this template matching module?
- Use template matching first to find the most plausible answer. Then, use the inference engine to produce the best possible explanation.
- Use template matching to add links in the inference graphs (whenever deductive inference fails).
- Implement Approach B as a standalone method for answering questions.</b>
To Do
- System building
- 1. Implement "template matching" using the ClueWeb corpus.
- 2. Continue system building.
- Create a derivation scorer stub. This will be replaced with a MLN or a BLP scorer.
- Test with iron nail example.
- 3. Jena API doesn't readily support multiple derivations.
- Ask Jena community to find out if this is possible.
- OWLIM as replacement.
- 4. Try out Tuffy MLN implemenatation.
- Use output of iron nail example
- If easy to use write wrappers around Tuffy to hook into our system.
- 5 Write evaluation code.
- Check with Peter.
- 6. Create a system architecture page with a figure and overview of the main components.
- Experiments
- 1. Run template matching approach as a baseline.
- 2. Run inference system as a baseline.
- Resource Collection