Learn More
In Information Extraction (IE), processing of named entities in text has traditionally been seen as a two-step process comprising a flat text span recognition sub-task and an atomic classification sub-task; relating the text span to a model of the world has been ignored by evaluations such as DARPA/NIST's MUC or ACE. However, spatial and temporal(More)
Recognizing spatial language in text documents, termed <i>geoparsing</i>, is useful for many applications, because together with mapping such language to lat/long values, also known as <i>geocoding</i>, it enables the connection of the unstructured textual realm with the structured realm of <i>Geographic Information Systems (GIS)</i> [11]. For example, news(More)
The task of named entity annotation of unseen text has recently been successfully automated with near-human performance. But the full task involves more than annotation, i.e. identifying the scope of each (continuous) text span and its class (such as place name). It also involves grounding the named entity (i.e. establishing its denotation with respect to(More)
We present improvements and modifications of the QED open-domain question answering system developed for TREC-2003 to make it cross-lingual for participation in the Cross-Linguistic Evaluation Forum (CLEF) Question Answering Track 2004 for the source languages French and German and the target language English. We use rule-based question translation extended(More)