We are glad to start our Fall2010 CUNY-NLP seminar series by two short talks by our own outstanding students Suzanne Tamang and Adam Lee. Time: 2pm-3pm, Friday, Oct 1 Place: Room 4102, CUNY Graduate Center, 365 Fifth Ave (34str&35str). Speaker: Suzanne Tamang Title: Adding Smarter Systems instead of Human Annotators: A Combined Approach to Slot Filling Abstract: The TAC-KBP2010 Slot Filling task requires a system to automatically distill information from a large document collection and return answers for a query entity with specified attributes (slots), and use them to expand the Wikipedia infoboxes. We describe two bottom-up Information Extraction style pipelines and a top-down Question Answering style pipeline to address this task. We propose several novel approaches to enhance these pipelines, including Wikipedia redirect link mining based query expansion, statistical answer re-ranking and Markov Logic Networks based cross-slot reasoning. We demonstrate that our system achieves 3.1% higher precision and 2.6% higher recall compared with the best system in the KBP2009 evaluation. In addition, we investigate the annotation challenges associated with this task and find that a single human annotator can only reach less than 50% recall; adding human annotators improved the coverage but easily converged to some recall upper-limit. We further propose a novel approach on combining annotations across top automated and human-systems. Surprisingly, filtering errors from system combination achieves higher relative gains in recall and is less costly than asking human annotators to conduct exhaustive search from scratch. This is based on the joint work with Zheng Chen, Adam Lee, Xiang Li, Marissa Passantino and Heng Ji at CUNY. Speaker: Adam Lee Title: Enhancing Multi-lingual Information Extraction via Cross-Media Inference and Fusion Abstract: We describe a new information fusion approach to integrate facts extracted from cross-media objects (videos and texts) into a coherent common represen-tation including multi-level knowledge (concepts, relations and events). Beyond standard information fusion, we exploited video extraction results and sig-nificantly improved gender detection from texts. We further extended our methods to multi-lingual environment (English, Arabic and Chinese) by presenting a case study on cross-lingual comparable corpora acquisition based on video comparison. This is based on the joint work with Marissa Passantino and Heng Ji at CUNY, and Guojun Qi and Thomas Huang at UIUC.