1. Meaning-Oriented Question-Answering with Ontological Semantics An AQUAINT Project from ILIT

2. CRL is a research department in the School of Arts and Sciences at NMSU Funded externally Currently has a staff of 10 PhDs Mainly focuses on language engineering research Languages include – Arabic, Farsi, Turkish, Spanish, Chinese, Japanese, KoreanLanguages

3. Advanced-technology company in Ithaca, New York Founded in 1990 by Dr. Richard Kittredge, Dr. Tanya Korelsky, and Dr. Owen Rambow. Goal is to transform results from research in natural language processing into practical software applications. Has developed a core set of text generation tools Current focus is on expanding the range of applications for this technology, with a particular focus on the Web.

4. The Institute for Language and Information Technologies at University of Maryland Baltimore County Sergei Nirenburg, Director Begins operation in September 2002 with a team of 3 senior personnel Close collaboration with NMSU CRL ILIT

5. Recent Projects: CRL CREST: Cross-Language Retrieval, Extract-ion, Summarization and Translation (a TIDES project) An Arabic-English Translation System (a TIDES project) MINDS: multilingual summarization Keizai, MINDSEYE: cross- language retrieval FLAX: HTML parsing Shiraz: Farsi-English, Dari-English MT Expedition: Rapid Ramp-Up of MT for Low Density Languages

6. Recent Projects: CoGenTex Production of user directed multi-document summaries (RIPTIDES) Multimedia display will include fluent English responses coordinated with tables, diagrams, and hypertext follow-up (Reporter) Deep generation techniques that employ an explicit representation of communicative structure (FoG and LFS) Rule based text generation tools, both for answer planning and syntactic generation (Exemplars and RealPro)

7. Meaning-Oriented Question-Answering with Ontological Semantics Domain: travel and meetings –question understanding and interpretation; – determining the answer and – presenting the answer two kinds of data source –open text (in English, Arabic and one of Persian, Russian or Spanish) –Structured Fact Database containing instances of ontological entities

8. Project Tasks Design and Implementation of System Architecture Knowledge Acquisition Question Understanding Question Interpretation Answer Determination Answer Formulation Documentation; User and Evaluator Training; Testing; and System Evaluation

9. Dialog and Self- Awareness-related Answer Determination: (for running commentary and workflow and context- related communication) Question Interpretation:  task context  dialog context  user profile  analyst team profile Question Understanding Answer Formulation and Presentation Input : User Question in English Output : System Response in English Task-Oriented Answer Determination from Fact Database: IE from Fact Database NL Query Generation: in English, Arabic and one of Persian, Russian, Spanish Answer Determination from open text:  IR  IE  Production of TMRs for Textual FIllers of IE Templates NL Query Fact DatabaseFact Database: including instances of goals, plans, scripts Ontology: including goals, plans, scripts LexiconsLexicons for Each Language in System: including names and phrases Static Knowledge Sources Processing Modules and Intermediate Results Goal and Plan Processing Manager System Working Memory Extended TMR: adds a statement of active goals, plans and scripts in the system System Response in TMR Basic Text Meaning Representation (TMR) Goal Attainment and Plan Execution Agenda

10. Development Strategy Rapid Prototyping Using pre-existing components Evaluation of end-to-end system performance for specific tasks

11. Deliverables A QA system in the domain of travel and meetings, with a capability to search for information in open texts in three languages and in a structured, ontology-based Fact DB; an enhanced text analysis system for each of the languages; a question interpretation module that takes into account user goals and the context of the dialog; an integrated IR/IE module working on open text in three languages, on the basis of ontologically defined extraction templates;

12. Deliverables (Cont.) an ontology of about 6,500 concepts; A Fact DB of about 100,000 facts; a system for automating the acquisition of the Fact DB; a semantic lexicon for each of the languages in the system, at about 20,000 entries a decision-making module that determines the answer(s) and system action(s) at each step of the dialog/task processing; an ontological-semantic text generation module.

13. Sergei Nirenburg sergei@crl.nmsu.edusergei@crl.nmsu.edu Jim Cowiejcowie@crl.nmsu.edujcowie@crl.nmsu.edu Tanya Korelskytanya@cogentex.comtanya@cogentex.com Richard Kittredgerichard@cogentex.comrichard@cogentex.com

14. Structured Common Fact Database Uniform format for all kinds of data Uniform support for multiple applications and tools Semantically anchored in general ontology Constantly updated; today, manually to semi-automatically; tomorrow, automatically Supports both domain knowledge and workflow specification

15. FACT DATABASE: The “Asian-Nation” Instance: “Turkey”

17. Ontology Defined An ontology is a formally and semantically defined repository of concepts and relations about the world. –Including knowledge about events, objects, and work flow scripts Linked to the ontology are: –fact databases, including facts about actual events, objects, places, personalities, etc. –“onomastica”, or multilingual proper name lists

19. LEXICON: English lexical entry mapped to concept “EXIT”

20. LEXICON: Chinese lexical entry mapped to concept “EXIT”

21. Travel Tracking Template PERSON-TRAVELLING NAME ALIAS NATIONALITY AFFILIATION POSITION PURPOSE-OF-TRAVEL(attend meeting of world leaders) DESTINATION(location of meeting) FLIGHT-INFORMATION departure from departure time arrival at arrive time flight number

22. Text Meaning Representation Output: proposition _1 –head %travel_1 agent human_544“Hakan Sukur” source location_23“London” destination location_25“Istanbul” means flight-17776“BA633” –tmr-time time-begin 20000702“March 2, 2002” –aspect iteration single; phase end… “departed” Input: Hakan Sukur arrived in Istanbul from London on British Airways Flight 633 on March 2, 2002