Information Extraction Discipline

From GM-RKB
Jump to: navigation, search

See: Scientific Discipline, Information Extraction, Information Retrieval Discinpline, Information Extraction Subject Area, Information Extraction Task, Information Extraction Algorithm, Information Extraction System.



References

  • (Wikipedia, 2009) ⇒ http://en.wikipedia.org/wiki/Information_extraction
    • In natural language processing, information extraction (IE) is a type of information retrieval whose goal is to automatically extract structured information, i.e. categorized and contextually and semantically well-defined data from a certain domain, from unstructured machine-readable documents. An example of information extraction is the extraction of instances of corporate mergers, more formally MergerBetween(company1,company2,date), from an online news sentence such as: "Yesterday, New-York based Foo Inc. announced their acquisition of Bar Corp." A broad goal of IE is to allow computation to be done on the previously unstructured data. A more specific goal is to allow logical reasoning to draw inferences based on the logical content of the input data.
    • The significance of IE is determined by the growing amount of information available in unstructured (i.e. without metadata) form, for instance on the Internet. This knowledge can be made more accessible by means of transformation into relational form, or by marking-up with XML tags. An intelligent agent monitoring a news data feed requires IE to transform unstructured data into something that can be reasoned with.
    • Typical subtasks of IE are:
      • Named Entity Recognition: recognition of entity names (for people and organizations), place names, temporal expressions, and certain types of numerical expressions.
      • Coreference: identification chains of noun phrases that refer to the same object. For example, anaphora is a type of coreference.
      • Terminology extraction: finding the relevant terms for a given corpus
      • Relationship Extraction: identification of relations between entities, such as:
        • PERSON works for ORGANIZATION (extracted from the sentence "Bill works for IBM.")
        • PERSON located in LOCATION (extracted from the sentence "Bill is in France.")