In TREC 2007, Language Computer Corporation explored how a new, semantically-rich framework for information retrieval could be used to boost the overall performance of the answer extraction and answer selection components featured in its CHAUCER-2 automatic question-answering (Q/A) system. By replacing the traditional keyword-based retrieval system used in (?) with a new indexing and retrieval engine capable of retrieving documents or passages based on the distribution of named entities or semantic dependencies, we were able to dramatically enhance CHAUCER-2’s overall accuracy, while significantly reducing the number of of candidate answers that were considered by its Answer Ranking and Answer Validation modules.