3.  Motivation:  Actor: [awards, height, age, weight, birthdate, birthplace, cause of death, real name]  Painter: [paintings, biography, bibliography, autobiography, artwork, self portraits, quotations, bio, quotes, life history].

5.  Labeled Classes of Instances: - Similarly to [9], the extraction of labeled classes of instances relies on hand-written patterns, widely used in literature on extracting conceptual hierarchies from text

6.  Attributes of Labeled Classes of Instances 1. word 2. construction of internal search 3. construction of a reference internal search 4. ranking

7.  Conceptual Hierarchies: - Manually-constructed language resources such as WordNet provide reliable, wide-coverage upper-level conceptual hierarchies, by grouping phrases with the same meaning

8.  Similar-Sense Selection 1. synonyms 2. siblings, or coordinate terms 3. immediate superconcepts, or hypernyms 4. immediate subconcepts, or hyponyms available in the WordNet hierarchies around that sense

9.  Hierarchical Propagation - As mentioned earlier, a labeled class is accompanied by a ranked list of attributes extracted from query logs.  Coverage-Based Attribute Specificity

11.  Hierarchical Attributes

12.  This paper introduces an extraction framework for exploiting labeled classes of instances acquired from a combination of documents and search query logs, to extract attributes over conceptual hierarchies.

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