FASTUS System

A FASTUS System is an Information Extraction System based on ...

• AKA: Finite State Automaton Text Understanding System.
• Context:
  • It was developed at SRI International.
  • It makes use of Cascading FSTs
  • It can involve a Named Entity Recognition Task.
  • It can recognize Noun Groups and Verb Groups.
  • It can construct Complex Noun Groups and Complex Verb Groups.
  • It can identify patterns of interest
  • It can identify and merge event structures
• See: Information Extraction.

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References

• http://www.ai.sri.com/~appelt/fastus.html
  • FASTUS is a (slightly permuted) acronym for Finite State Automa-based Text Understanding System. It is a system for extracting information from free text. Currently English and Japanese versions of the system exist. Typically, applications mark text with annotations that indicate items of interest, such as names of people or companies, or it fills templates with information that could be entered into a relational database. FASTUS works as a series of cascaded, finite-state automata.
  • Buried by an avalanche of text. FASTUS was developed in response to the needs of the government intelligence community for scanning and processing huge volumes of written texts. Government intelligence agencies collect much information from around the world from both classified and unclassified sources. Assimilating important facts from this data can be a daunting task for an analyst. One analyst had described the problem by saying that, “If I read every bit of information that might be important to what I am working on, it would be like reading War and Peace every day. FASTUS provides the analyst with a tool that will help him or her to avoid being overwhelmed by the flood of information.
  • FASTUS is most appropriate for information extraction tasks, rather than full text understanding. That is, it is most effective for tasks in which (1) only a fraction of the text contains relevent information, and (2) there is a relatively simple, predefined, rigid target representation that the information is mapped into.
  • FASTUS has been under development since (1992). The system is implemented in Common Lisp, and has been transported to several hardware platforms.

1996

• (Hobbs et al, 1996) ⇒ Jerry R. Hobbs, Douglas Appelt, John Bear, David Israel, Megumi Kameyama, Mark Stickel, and Mabry Tyson. (1996). “FASTUS: A Cascaded Finite-State Transducer for Extracting Information from Natural-Language Text.” In: Roche and Schabes, eds., Finite-State Language Processing., MIT Press.

1995

• (Appelt et al, 1995) ⇒ Douglas E. Appelt, Jerry R. Hobbs, John Bear, David Israel, Megumi Kameyama, Andy Kehler, David Martin, Karen Meyers, and Mabry Tyson. (1995). “SRI International FASTUS system: MUC-6 test results and analysis.” In: Proceedings of the Sixth Message Understanding Conference (MUC-6).

1993

• (Appelt et al, 1993) ⇒ Douglas E. Appelt, Jerry R. Hobbs, John Bear, David J. Israel, and Mabry Tyson. (1993). “FASTUS: A Finite-state Processor for Information Extraction from Real-world Text.” In: Proceedings of the Thirteenth International Joint Conference on Artificial Intelligence (IJCAI-93).

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