PPT-Focused Entailment Graphs for Open IE Propositions

Omer Levy Ido Dagan Jacob Goldberger Bar Ilan University Israel Open IE Extracts propositions from text which makes aspirin relieve headaches No supervision No predefined schema. Peter Clark. Allen Institute for Artificial Intelligence (AI2). Mission: . achieve scientific breakthroughs by constructing AI systems with reasoning, learning, and reading capabilities. . 2. Overall Goals. University . of. . Rome. “Tor Vergata”. Roma, Italy. Textual Entailment Recognition for Web Based Question-Answering. Operational. . Scenarios. What’s. the . weather. in Macao?. When. . is. Resources: . A Survey of Paraphrasing and Textual Entailment . Methods. . . . Androutsopoulos. and . Malakasiotis. Natural Language and Meaning. Meaning. Language. Ambiguity. Recap. Common . Three-Way Equivalence:. Sentence . meanings. The objects of the attitudes. The referents of ‘that’-. clauses. We can call whatever is all of these things a “proposition.” Now we have the question: what are propositions?. What you need to do:. Enroll to tuomas.j.lahtinen@aalto.fi, course is open for everyone - no prerequisites!. Show up in lecture hall M232 (M1) on Monday 19.5. at 10 o’clock.. 19.5. .-26.5.. QA4MRE, . and Machine Reading. Peter Clark. Vulcan Inc.. What is . Machine Reading?. Not (just). parsing + word senses. Construction of a . coherent representation. of the scene the text describes. Randy . Goebel. Alberta Innovates Centre for Machine Learning. Department of Computing Science. University of Alberta. Edmonton, Alberta . Canada. rgoebel@ualberta.ca. Fuji-san. BIRS. Science or Engineering?. (Excitement Project). Bernardo Magnini. (on behalf of the Excitement consortium). 1. STS workshop, NYC March 12-13 2012. Excitement Project. EXploring. Customer Interactions through Textual . EntailMENT. Daniel R. Schlegel and Stuart C. Shapiro. Department of Computer Science and Engineering. University at Buffalo, The State University of New York. Buffalo, New York, USA. <. drschleg,shapiro. >@buffalo.edu. Board Talk Wrap Up. What do we know about the characters and how?. Discuss your board at your table with this question in mind.. Character and Theme. Categorize/Group these characters. What themes is Austen setting up through her characters?. Peter Clark. Allen Institute for Artificial Intelligence (AI2). Mission: . achieve scientific breakthroughs by constructing AI systems with reasoning, learning, and reading capabilities. . 2. Overall Goals. Open-IE . meets . Knowledge . Representation. Ido Dagan. Bar-. Ilan. University, Israel. Knowledge Representation (KR). Two complementary frameworks:. Knowledge graphs. Formal pre-specified schema & predicates. Semantics Unit 2 Part 2. A Sentence. A grammatically complete series of words that expresses a complete thought.. S + V + expresses a complete thought. I would like a cup of coffee . is a sentence. . 1. A . deductive argument . is one that claims to establish its conclusion conclusively. . A . valid. deductive . argument is one in which, if all the premises are true, the conclusion must . be true.