18. A method in a computer system for extracting relational information from a corpus of text, the relational information including tuples having a first entity, a relationship indicator, and a second entity, and the relationship indicator indicating a relationship between the first entity and the second entity, the method comprising: providing a classifier for determining whether the relationship indicator of a tuple indicates a correct relationship between the first entity and the second entity based on features of the tuple, the classifier being generated 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; identifying syntactic information of words of the corpus; identifying a candidate tuple from the corpus based on the syntactic information of the words of the corpus, the relationship indicator of the candidate tuple including a word from the corpus describing the relationship between the first entity and the second entity; extracting features of the candidate tuple; and applying the classifier to the extracted features of the candidate tuple to determine whether the relationship indicator of the candidate tuple indicates a correct relationship between the first entity and the second entity of the candidate tuple.
19. The method of claim 18 wherein the syntactic information is a part-of-speech.