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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)
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)
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)
We present our new statistically-inspired open-domain Q&A research system that allows to carry out a wide range of experiments easily and flexibly by modifying a central file containing an experimental " recipe " that controls the activation and parameter selection of a range of widely-used and custom-built components. Based on this, we report our(More)