Charles P. Dolan

Tensor Product Production System: a Modular Architecture and Representation

Can connectionist networks effectively represent and process structure? A technique called ‘tensor product representations’, which formalizes and generalizes the approaches of several previous conn...

UMass/Hughes: description of the CIRCUS system used for MUC-5

The primary goal of our effort is the development of robust and portable language processing capabilities for information extraction applications. The system under evaluation here is based on language processing components that have demonstrated strong performance capabilities in previous evaluations [Lehnert et al. 1992a]. Having demonstrated the general viability of these techniques, we are now concentrating on the practicality of our technology by creating trainable system components to replace hand-coded data and manually-engineered software.

Hughes Trainable Text Skimmer: description of the TTS system as used for MUC-3

The objective of the Hughes Trainable Text Skimmer (TTS) Project is to create text skimming software that: (1) can be easily re-configured for new applications, (2) improves its performance with use, and (3) is fast enough to process megabytes of text per day. The TTS-MUC3 system is our first full scale prototype.

Hughes Research Laboratories: description of the Trainable Text Skimmer used for MUC-4

The objective of the Hughes Trainable Text Skimmer (TTS) Project is to create text skimming software that: (1) can be easily re-configured for new applications, (2) improves its performance with use, and (3) is fast enough to process several megabytes of text per day. The TTS-MUC4 system is our second full-scale prototype. It is an adaptation of the TTS-MUC3 system [1] [2], which constituted our first-full scale text skimming prototype.

UMass/Hughes TIPSTER project on extraction from text

The primary goal of our effort is the development of robust and portable language processing capabilities and information extraction applications. Our system is based on a sentence analysis technique called selective concept extraction. Having demonstrated the general viability of this technique in previous evaluations [Lehnert, et al. 1992], we are now concentrating on the practicality of our technology by creating trainable system components to replace hand-coded data and manually-engineered software.

Hughes research laboratories Trainable Text Skimmer: MUC-4 test results and analysis

Table 1 shows the official template-by-template score results for the Hughes Trainable Text Skimmer used for MUC-4 (TTS-MUC4) on TST3. TTS is a largely statistical system, using a set of Bayesian classifiers with the output of a shallow parser as features. (See the System Summary section of this volume for a detailed description of TTS-MUC4).