Difference between revisions of "Vulcan/PrototypeToWorking"
From Knowitall
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* Integrate with textual evidence finder. | * Integrate with textual evidence finder. | ||
− | <span style="background-yellow">ETC: Friday, Sept 13th</span> | + | <span style="background-color:yellow">ETC: Friday, Sept 13th</span> |
== Actual evidence == | == Actual evidence == |
Revision as of 20:24, 6 September 2013
The following is a todo list for converting the prototype system into a working system that can operate on arbitrary input propositions. There are four main items:
- Switch to using real evidence instead of hand-written axioms. This means using the tuple database that Greg has built.
- Use external procedure calls to allow for dynamic verification of predicates.
- Writing a translator that can convert rules into Tuffy's MLN format.
- Integrate with textual evidence finder.
ETC: Friday, Sept 13th
Actual evidence
- Open IE tuples
- We need to handle nested relations and arguments with complex internal structure. (Examples here.)
- Open IE 4.0 handles n-ary but not nesting. [Michael will add post-processing to output nested tuples]
- We need a higher coverage version of Open IE that correctly handles internal structure in a complex argument.
- Convert Open IE tuples into Tuffy's MLN axiom format.
- Decide on stemming, head word extraction and other normalization to apply.
- Import into postgres db.
- WordNet
- Convert WordNet RDF triples into Tuffy's MLN format.
- Import into postgres db.
- Compound Noun Categorizer (CNC) [Stopgap arrangement until Postgres external procedure is figured out.]
- Process arguments (phrases) in propositions and study guide through CNC.
- Extract relations that denote containment (e.g., "composed of")
- Import into postgres db.
- Figure out external procedures.
- Will do this early next week.
Rules
- Examples provide a starting point.
- Need to write a converter that translates human readable rules into MLN format.
- How to assign weights to the rules?
Propositions
- Extract best proposition.
Textual Evidence Finder
- Take output from TEF and convert it into a single MLN inference rule.