FASTUS: A Finite-state Processor for Information Extraction from Real-world Text

Approaches to text processing that rely on parsing the text with a context-free grammar tend to be slow and error-prone because of the massive ambiguity of long sentences. In contrast, FASTUS employs a nondeterministic finite-state language model that produces a phrasal decomposition of a sentence into noun groups, verb groups and particles. Another finite-state machine recognizes domain-specific phrases based on combinations of the heads of the constituents found in the first pass. FASTUS has been evaluated on several blind tests that demonstrate that state-of-the-art performance on information-extraction tasks is obtainable with surprisingly little computational effort.

• Type: Conference
• Year: 1993
• Where: IJCAI
• Authors: Douglas E. Appelt, Jerry R. Hobbs, John Bear, David J. Israel, Mabry Tyson
• Keywords: Context-free Grammar Tend, IJCAI 1993, IJCAI 2007, Nondeterministic finite-state Language, Phrasal Decomposition