Search (1 results, page 1 of 1)

0.027950348 = product of:
  0.055900697 = sum of:
    0.055900697 = product of:
      0.11180139 = sum of:
        0.11180139 = weight(_text_:light in 3403) [ClassicSimilarity], result of:
          0.11180139 = score(doc=3403,freq=2.0), product of:
            0.2920221 = queryWeight, product of:
              5.7753086 = idf(docFreq=372, maxDocs=44218)
              0.050563898 = queryNorm
            0.3828525 = fieldWeight in 3403, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              5.7753086 = idf(docFreq=372, maxDocs=44218)
              0.046875 = fieldNorm(doc=3403)
      0.5 = coord(1/2)
  0.5 = coord(1/2)

Abstract

We present YAGO, a light-weight and extensible ontology with high coverage and quality. YAGO builds on entities and relations and currently contains more than 1 million entities and 5 million facts. This includes the Is-A hierarchy as well as non-taxonomic relations between entities (such as hasWonPrize). The facts have been automatically extracted from Wikipedia and unified with WordNet, using a carefully designed combination of rule-based and heuristic methods described in this paper. The resulting knowledge base is a major step beyond WordNet: in quality by adding knowledge about individuals like persons, organizations, products, etc. with their semantic relationships - and in quantity by increasing the number of facts by more than an order of magnitude. Our empirical evaluation of fact correctness shows an accuracy of about 95%. YAGO is based on a logically clean model, which is decidable, extensible, and compatible with RDFS. Finally, we show how YAGO can be further extended by state-of-the-art information extraction techniques.