Lexical Network Theory (Computer and Information Science)
{'Code': '05020000', 'Directorate': {'Abbreviation': 'CSE', 'LongName': 'Direct For Computer & Info Scie & Enginr'}, 'Division': {'Abbreviation': 'IIS', 'LongName': 'Div Of Information & Intelligent Systems'}}
{'SignBlockName': 'Howard Moraff', 'PO_EMAI': None, 'PO_PHON': None}
This research develops a new approach to the lexicon, using             network structures to describe the relationships between the                    alternative meanings of words. In traditional theories of the                   lexicon, these various meanings are simply listed, as though                    there were no further lexical structure present. Recent                         linguistic research suggests, however, that the lexicon is very                 highly structured, in ways not modeled by traditional approaches.               This investigation clarifies lexical network structure in much                  more detail than has previously been done, and models these                     results in ways that will be useful to artificial intelligence                  researchers building computer systems for natural language                      processing.                                                                             The lexicon - the body of knowledge about words, their                  meanings, and how they are related - has recently become a focus                for intense research for natural language processing systems.                   The present project, a collaboration between researchers in                     artificial intelligence and linguistics, offers a new approach to               capturing knowledge about words.  The network approach is meant                 to be compact (due to a limited number of links allowed between                 meanings), yet powerful enough to substantially enhance the                     ability of computers to process natural language input and                      output.
{'FirstName': 'George', 'LastName': 'Lakoff', 'PI_MID_INIT': 'P', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'George P Lakoff', 'EmailAddress': None, 'NSF_ID': '000192105', 'StartDate': '07/01/1987', 'EndDate': None, 'RoleCode': 'Principal Investigator'}
{'Name': 'University of California-Berkeley', 'CityName': 'BERKELEY', 'ZipCode': '947101749', 'PhoneNumber': '5106433891', 'StreetAddress': '1608 4TH ST STE 201', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'California', 'StateCode': 'CA', 'CONGRESSDISTRICT': '12', 'CONGRESS_DISTRICT_ORG': 'CA12', 'ORG_UEI_NUM': 'GS3YEVSS12N6', 'ORG_LGL_BUS_NAME': 'REGENTS OF THE UNIVERSITY OF CALIFORNIA, THE', 'ORG_PRNT_UEI_NUM': None}
{'Name': None, 'CityName': None, 'StateCode': None, 'ZipCode': None, 'StreetAddress': None, 'CountryCode': None, 'CountryName': None, 'StateName': None, 'CountryFlag': None, 'CONGRESSDISTRICT': None, 'CONGRESS_DISTRICT_PERF': '""'}
{'Code': '6856', 'Text': 'ARTIFICIAL INTELL & COGNIT SCI'}
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=1987&All=true', 'xml': '8703202.xml'}