Extended Semantic Tagging for Entity Extraction

We present results of a statistical method we developped for the detection of what we define as generalized named entities from manually transcribed conversations. This work is part of an ongoing project for an information extraction system in the field of maritime Search And Rescue (SAR). Our purpose is to automatically detect relevant words and annotate them with concepts from a SAR ontology. Our approach combines similarity score vectors and topical information. Similarity vectors are generated using a SAR ontology and the Wordsmyth dictionary-thesaurus. Evaluation is carried out by comparing the output of the system with key answers of predefined extraction templates. Results on speech transcriptions are comparable to those on written texts in MUC7.