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<Paper uid="M95-1012">
  <Title>MITRE: DESCRIPTION OF THE ALEMBIC SYSTEM USED FOR MUC-6</Title>
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MITRE:
DESCRIPTION OF THE ALEMBIC SYSTEM USED FOR MUC-6
</SectionTitle>
    <Paragraph position="0"> {aberdeen, john, clay, lynette, parann, mbv}@mitre.org As with several other veteran Muc participants, MITRE'S Alembic system has undergone a major trans formation in the past two years. The genesis of this transformation occurred during a dinner conversation at the last Muc conference, MUC-5 . At that time, several of us reluctantly admitted that our major impediment towards improved performance was reliance on then-standard linguistic models of syntax. We knew we would need an alternative to traditional linguistic grammars, even to the somewhat non-traditional categoria l pseudo-parser we had in place at the time. The problem was, which alternative ? The answer came in the form of rule sequences, an approach Eric Brill originally laid out in his work o n part-of-speech tagging [5, 7] . Rule sequences now underlie all the major processing steps in Alembic. part-of-speech tagging, syntactic analysis, inference, and even some of the set-fill processing in the Template Elemen t task (TE) . We have found this approach to provide almost an embarrassment of advantages, speed an d accuracy being the most externally visible benefits . In addition, most of our rule sequence processors ar e trainable, typically from small samples . The rules acquired in this way also have the characteristic that the y allow one to readily mix hand-crafted and machine-learned elements . We have exploited this opportunity t o apply both machine-learned and hand-crafted rules extensively, choosing in some instances to run sequence s that were primarily machine-learned, and in other cases to run sequences that were entirely crafted by hand .</Paragraph>
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