1. A method in a computer system for automatically extracting relational information from a corpus of text, comprising: generating a classifier to classify tuples as being trustworthy or not trustworthy by parsing sentences of a training corpus of text to identify training tuples, labeling the training tuples as trustworthy or not trustworthy based on whether the training tuples satisfy syntactic constraints as indicated by the parsing, extracting features of the training tuples, and training the classifier using the extracted features and the labels, a tuple including a first entity, a relationship, and a second entity; conducting, by the computer system, a single pass through the corpus of text to automatically extract a plurality of tuples from the corpus of text using a set of linguistic features and classifying the extracted tuples as being trustworthy or not trustworthy by extracting features of the extracted tuples and applying the classifier to the extracted tuples.
1. A method in a computer system for automatically extracting relational information from a corpus of text, comprising: generating a classifier to classify tuples as being trustworthy or not trustworthy by parsing sentences of a training corpus of text to identify training tuples, labeling the training tuples as trustworthy or not trustworthy based on whether the training tuples satisfy syntactic constraints as indicated by the parsing, extracting features of the training tuples, and training the classifier using the extracted features and the labels, a tuple including a first entity, a relationship, and a second entity; conducting, by the computer system, a single pass through the corpus of text to automatically extract a plurality of tuples from the corpus of text using a set of linguistic features and classifying the extracted tuples as being trustworthy or not trustworthy by extracting features of the extracted tuples and applying the classifier to the extracted tuples. 5. The method of claim 1 wherein the entities include nouns.