Natural Language Processing Semantics 0 Flakey

Semantics How it should not be.

My Chat with A.L.I.C.E. Human: hello. ALICE: Hi there! Human: how are you? ALICE: I am functioning within normal parameters. Human: good. ALICE: What do you really want to talk about? Human: about you. ALICE: Me? Human: yes. ALICE: Aw.

Human: how are you? ALICE: Everything is going extremely well. Human: good. ALICE: Thanks for the compliment. Human: do you have a grammar? ALICE: Doesn't everyone have a grammar. I have a lot of friends on the Internet. Human: what friends? ALICE: Are you using Netscape or Explorer? Human: feature structures. ALICE: Do you have any conditions I should know about?

Web References repository/ai/areas/classics/eliza/0.htmlhttp:// /afs/cs/project/ai- repository/ai/areas/classics/eliza/0.html

Semantics How it could be.

Flakey - Example  Flakey as Communicating Agent  Case Frame Representation  Concrete and Generic Actions  Effects of Actions  Inference / Reasoning  Two Types of Questions

"Flakey, bring this file to Karen." listener verb determiner noun preposition noun V NP PP NounPhrase Prepos. Phrase head direct object indirect object agent action patiens recipient Flakey as Communicating Agent

Case Frames for Representing NL "Flakey, bring this file to Karen.” verb NounPhrase PPhrase head direct object indirect object case frame action: bringheadverb patiens: this filedirect object recipient: to Karen indirect object manner: now modifier- added-

Mapping Case Frames to Actions case frame agent:Flakey action: bringhead patiens: this filedirect object recip.: to Karen indirect object robot action precondition: have (Flakey, file1) action: bring (Flakey, file1, Karen) effect: not (have (Flakey, file1)) and have (Karen, file1)

Concrete and Generic Actions I robot concrete action (instance of action) precondition: have (Flakey, file1) action: bring (Flakey, file1, Karen) effect: not (have (Flakey, file1)) and have (Karen, file1) robot generic action (concept in KB) precondition: have (agent, object) action: bring (agent, object, recipient) effect: not (have (agent, object)) and (have (recipient, object))

Concrete and Generic Actions II generic action: bring (agent, object, recipient) precondition: have (agent, object) effect: not (have (agent, object)) and (have (recipient, object)) instance of action: bring (Flakey, file1, Karen) precondition: have (Flakey, file1) effect: not (have (Flakey, file1)) and have (Karen, file1) You may add objects as features to action-frame.

Effects of Actions instance of action: bring (Flakey, file1, Karen) precondition: have (Flakey, file1) effect: not (have (Flakey, file1)) and have (Karen, file1) effect of this action delete from KB have (Flakey, file1) add to KB have (Karen, file1) preconditions and effects are formulae describing world states, related to the‘dynamic KB’.

Flakey - Reasoning, Inference Integrate General Rules (Proper Axioms; Theory) Axiom  x  y  loc: (have(x,y)  (at(x,loc)  at(y,loc))) Reasoning / Inference have (Flakey, object)  at (Flakey, here)  at (object, here)

Flakey - Question Answering I “Flakey, where did you bring the file.” case frame action: bring patiens: file1 destination: ? Compare to stored case frames: case frame action: bring patiens: file1 destination: Karen Conclusion and answer: “I brought the file to Karen.”

Flakey - Question Answering II Q: “Flakey, where is the file.” case frame action/status: is subject: the fileidentify with file1 location: ? refers to loc of file1 Access dynamic KB (world state) Stored from effect of bring-action or pre-stored:... at (file1, Karen),... have (Karen, file1),... A: “The file is at Karen.” or "Karen has the file."