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We present a natural language interface system which is based entirely on trained statistical models. The system consists of three stages of processing: parsing, semantic interpretation, and discourse. Each of these stages is modeled as a statistical process. The models are fully integrated, resulting in an end-to-end system that maps input utterances into(More)
This paper describes results of an experiment with 9 different DARPA Communicator Systems who participated in the June 2000 data collection. All systems supported travel planning and utilized some form of mixed-initiative interaction. However they varied in several critical dimensions: (1) They targeted different back-end databases for travel information;(More)
Arabic Dialects present many challenges for machine translation, not least of which is the lack of data resources. We use crowdsourc-ing to cheaply and quickly build Levantine-English and Egyptian-English parallel corpora , consisting of 1.1M words and 380k words, respectively. The dialectal sentences are selected from a large corpus of Arabic web text, and(More)
This paper describes the evaluation methodology and results of the 2001 DARPA Communicator evaluation. The experiment spanned 6 months of 2001 and involved eight DARPA Communicator systems in the travel planning domain. It resulted in a corpus of 1242 dialogs which include many more dialogues for complex tasks than the 2000 evaluation. We describe the(More)
Production of parallel training corpora for the development of statistical machine translation (SMT) systems for resource-poor languages usually requires extensive manual effort. Active sample selection aims to reduce the labor , time, and expense incurred in producing such resources, attaining a given performance benchmark with the smallest possible(More)
We propose a distinction between two kinds of metonymy: "referential" metonymy, in which the refer-ent of an NP is shifted, and "predicative" metonymy, in which the referent of the NP is unchanged and the argument place of the predicate is shifted instead. Examples are, respectively, "The hamburger is waiting for his check" and "Which airlines fly from(More)
We describe the rst sentence understanding system that is completely based on learned methods both for understanding individual sentences, and determinig their meaning in the context of preceding sentences. We describe the models used for each of three stages in the understanding: semantic parsing, semantic classication, and discourse modeling. When we ran(More)
We report on experiments to measure the effect of speech recognition errors and automatic punctuation insertion errors on the performance of information extraction (entity and relation extraction). The outputs of several recognition systems with a range of word error rates (WER), along with punctuation insertion, were fed into a system that extracts(More)