1. Knowledge-Based Question-Answering Bruce Porter, Peter Clark, and John Thompson

2. Terminology and Key Points Knowledge base - a formal representation of knowledge with associated inference methods Explanation Generation = select, organize, and present information to answer a question. Inference plays a supporting role in each step. Key Points: –Ways of evaluating explanation systems –Architectural principles for explanations systems –Composition: a way to reduce the up-front “knowledge requirement”

3. Botany Knowledge Base 10 year effort by full-time domain expert and support staff contains 20,000 concepts and 100,000 facts much more information available via inheritance and rules performance goal: robust, expert-level ability to answer questions with good explanations

4. An Example of Explanation Generation: The KNIGHT System (J. Lester and B. Porter, Developing and Empirically Evaluating Robust Explanation Generators, Computational Linguistics Journal, 23(1), 1997.) Q: What happens during embryo sac formation? A: Embryo sac formation is a kind of female gametophyte formation. During embryo sac formation, the embryo sac is formed from the megaspore mother cell. Embryo sac formation occurs in the ovule. Embryo sac formation is a step of angiosperm sexual reproduction. It consists of megasporogenesis and embryo sac generation. During megasporogenesis, the megaspore mother cell divides in the nucellus to form 4 megaspores. During embryo sac generation, the embryo sac is generated from the megaspore.

5. KNIGHT approach: 1. Representation: of the situation which user is asking about 2. Elaboration: of that representation, guided by an answer schema (EDP) 3. Assembly: of results into natural language text 4. Presentation

6. Knight System Architecture (virtual) KB provided by base facts BKB views view retriever explanations KNIGHT... worked well to provide an “arms length relationship” between application programs and the KB user requests information

7. View Retriever (L. Acker and B. Porter, Extracting Viewpoints from Knowledge Bases, AAAI-94) given a specification of desired information return a subgraph of the knowledge base representing a coherent, comprehensive set of facts pertinent to the specification

8. The Viewpoint of Photosynthesis as Production (L. Acker and B. Porter, Extracting Viewpoints from Knowledge Bases, AAAI-94) Production Substance Place Thing Substance Thing product location energy source raw materials producer Chloroplast ATP Water Carbon-Dioxide Photosynthetic Cell Photosynthesis Oxygen Glucose product location energy source raw materials producer

9. A Combination Viewpoint: Flower Structure vis-à-vis Plant Reproduction Angiosperm Sexual Reproduction Pollen Grain Formation Embryo Sac Formation Pollen Grain Transfer Pollen Grain Germination Double Fertilization FlowerAndroecium Gynoecium subevents location has parts surrounds location destination location source

10. Explanation Design Plan for Processes Explain Process Process Overview Fates of patients Temporal information Process details As-kind-of viewpoint Black-box viewpoint Location description For each patient: change viewpoint Temporal step-of viewpoint Temporal steps viewpoints For each subevent: Black-box viewpoint Nodes contain programs with iteration and conditionals

11. KNIGHT Evaluation Questions (60) KNIGHTBiologist Panel of Judges: 8 Biologists (60)(15) explanations Evaluations

12. Results of the Evaluation Author Overall Content Organization Writing Correctness KNIGHT 2.37±0.13 2.65±0.13 2.45±0.16 2.40±0.13 3.07±0.15 Human 2.85±0.15 2.95±0.16 3.07±0.16 2.93±0.16 3.16±0.15 Overall Content Organization Writing Correctness Difference 0.48 0.30 0.62 0.53 0.09 T statistic -2.36 -1.47 -2.73 -2.54 -0.42 Significance 0.02 0.14 0.07 0.01 0.67 Significant? yes no no yes no

13. Another example (DCE Application) Describe a binding event, between - the client Payday running on Slowbox - the server Oracle running on Speedy Question (user): Answer (KB-generated): First, Payday queries the cell directory server for the network-id of Oracle. Then Payday queries the endpoint mapper of Speedy for Oracle’s endpoint. Finally, Payday assembles a binding from the network-id and the endpoint.

15. 1. Representation of situation in question Describe a binding event, between - the client Payday running on Slowbox - the server Oracle running on Speedy Binding-Event01 Payday OracleSpeedy client server host Slowbox host

16. subevents ? Binding-Event01 Payday OracleSpeedy client server host Slowbox 2. Elaboration (guided by answer schema) “For each subevent, present summary, and pointers to sub-subevents.” Schema/EDP (paraphased): Query02Query01Assemble01 then subevents agent queried request ? ? ? CDS01 Network01 network cds queried

17. Endpoint01NetId01 Endpoint Mapper01 agent endpoint id epm request queriedcomponents agent Query01Query02Assemble01 then subevents request CDS01 Network01 network cds queried 2. Elaboration (guided by answer schema) Binding-Event01 Payday OracleSpeedy client server host Slowbox “For each subevent, present summary, and pointers to sub-subevents.” Schema/EDP (paraphased):

18. Binding-Event01 Query01Query02Assemble01 Payday OracleSpeedy Endpoint01NetId01 Endpoint Mapper01 CDS01 Network01 client server network cds agent queried endpoint id epm then request queriedcomponents agent subevents request “First” (the agent of Query01) “queries” (the queried of Query01) “for” (the request of Query01) host Slowbox host 3. Assembly of text answer “First, Payday queries the cell directory server for the network-id of Oracle.”

19. 4. Presentation

20. The Application Environment (Hyperlinked text)(run-time generated pages)

21. Critique Approach used in Botany KB & three smaller applications Benefits: –Customized answers –Controllable level of detail –Flexibility (in theory) Well received, but: –KBs still highly incomplete –laborious to build –difficult to achieve reuse  want more modular approach

22. A Component-Based Approach to Knowledge-Base Construction 1. Component theories = abstract, reusable models 2. More specific concepts: specified as compositions 3. Inference = construct compositions as needed to answer questions. Obervation: Concept representations contain numerous abstractions Approach:

23. Lessons from a Dictionary... Car: a Vehicle for Passengers Vehicle: a Means for Transporting something Transport: to Move from one Place to another Specific concepts defined as compositions of abstract concepts  Move: to GoGo: to Move Most abstract concepts appeal to core, foundational theories 

24. 1. Component Theories A coherent, encapsulated system of concepts and relations Contains: –ontology (vocabulary of concepts and relations) –axioms (rules) relating these Provides semantics for these concepts in the KB Can define specific theories using general ones

25. Example: Electrical Circuits Electrical Circuit Carries electricity If closed circuit from Fuel Cell to Device, then Device is powered Switches can open/close the circuit Motor Fuel Cells Light Switches

26. Distribution-Network P I I C C P Carries transport-element If unblocked path from Producer to Consumer, then Consumer is supplied. connects is transitive …. Example: Electrical Circuits Electrical Circuit Carries electricity If closed circuit from Fuel Cell to Device, then Device is powered Switches can open/close the circuit Motor Fuel Cells Light Switches

27. Distribution-Network P I I C C P Carries transport-element If unblocked path from Producer to Consumer, then Consumer is supplied. connects is transitive …. Electrical Circuit Carries electricity If closed circuit from Fuel Cell to Device, then Device is powered Switches can open/close the circuit Motor Fuel Cells Light Switches Circuits as Distribution Networks

28. Producers, Intermediaries, and Consumers are Nodes If unblocked path from Producer to Consumer, then Consumer is supplied.... Blockable-DAG P I I C C P Nodes can connect with other nodes. X reaches Y if X connects with Y. X reaches Z if X connects with Y and Y reaches Z …. Imports: Blockable-DAG And: Distribution-Network N1N2 N3 N4 N5 N6 Distribution Networks as DAGS

29. Ontology, compositions, basic facts about the domain Component theories in KB-PHaSE DAG Blockable DAG Distribution Network Processing Network Two-state Object Machines Discrete Event Model Electrical Circuits PHaSE KB Optical Circuits Spatial Relns

30. 2. Composition Describe domain-specific concepts as compositions: –a Bulb is a Resistor to Electricity producing Light –a Camera is a Device for the Recording of Images –a Battery is a Producer of Electricity –a Wire is a Conduit of Electricity Inference:compute properties of compound concept –using axioms from each component –on demand, in response to questions

31. ( Camera has (superclasses ( Device ))) (every Camera has (behavior ((a Recording with (input ( Image ))))) 2. Composition (example) Composition: Camera = a Device for the Recording of Images Recording Image Device behavior input Query: Failure modes of a camera?

32. ( Device has (superclasses ( Physobj ))) (every Device has (behavior ((a Activity ))) (failure-modes ( (the failure-modes of (the participants of the behavior of Self )))))) Activity Physobj Device Failure- Mode Failure- Mode failure- mode failure- mode failure- mode failure- mode behavior participants Physobj Component Theory: Devices Physobj part. Failure- Mode Failure- Mode failure- mode failure- mode failure- mode failure- mode Recording Image Device behavior input

33. Component Theory: Recording ( Recording has (superclasses ( Activity ))) (every Recording has (input ((a Signal ))) (participants ( (a Receptor with (input ((the input of Self )))... Recording Signal Receptor Memory-Unit ReceivingWriting Signal input agent subevents patient input output input participant Physobj part. Failure- Mode Failure- Mode failure- mode failure- mode failure- mode failure- mode Recording Image Device behavior input Receptor Memory-Unit ReceivingWriting Signal input agent subevents patient part. input output part.

34. Image Receptor Signal Recording Device behavior input Memory-Unit ReceivingWriting input agent subevents patient part. input output part. Failure- Mode Failure- Mode failure- mode failure- mode failure- mode failure- mode Run-Time Classification: Aperture = a Receptor of Images

35. Image Receptor Signal Recording Device behavior input Memory-Unit ReceivingWriting input agent subevents patient part. input output part. Failure- Mode Failure- Mode failure- mode failure- mode failure- mode failure- mode input output failure- mode Image Aperture Image Blockage Aperture - inputs an image - outputs an image - might be blocked -... input output failure- mode Image Aperture Image Blockage Run-Time Classification: Aperture = a Receptor of Images

36. Blockage Recording Device behavior input Receiving Writing agent subevents patient part. input part. failure- mode failure- mode failure- mode input output failure- mode Image Aperture Image Aging Memory-Unit input failure- mode Chemical sensitive-to covering Sheet Query: Failure modes of a camera? Blockage,... Sub-query: Participants in its behavior? Aperture,...

37. Compound Concepts are Ubiquitous –Botany: photosynthesis plant material distribution... –Aerospace: turbine gearbox assembly case drain fluid …(43k acronyms!)… –Sentences also: “The aircraft overshot the runway.” “The air-conditioning unit had no power.”...

38. Overall Architecture... Thing 1. Ontology 2-state Object Blckable DAG Process Network Distrn Network Optical Circuits Elec. Circuits Machine Discrete events 2. Component theories

39. Overall Architecture Blckable DAG Process Network Distrn Network Optical Circuits Elec. Circuits... Thing 1. Ontology 2. Component theories Camera = a Device for the Recording of Images 3. Definitions and Descriptions

40. Overall Architecture Blckable DAG Process Network Distrn Network Optical Circuits Elec. Circuits... Thing 1. Ontology 2. Component theories 4. Basic facts about domain PH. Science Checklists PH. Circuit PHaSE physical structure Camera =... 3. Definitions and Descriptions

41. Summary Explanation Generators select, organize, and present information in response to questions. Inference plays a supporting role in each step. Explanation Design Plans are built for each type of explanation. Composition at run-time reduces the up-front “knowledge requirement”

42. Discussion Technical: The component approach is still a work-in-progress; in particular although we can isolate the general theories, the “basic facts” can still be highly interdependent. Philosophical: We need a library of reusable components. Will the idiosyncrasies of real-world concepts overwhelm the generality of patterns?