Titlebook: Evaluation of Natural Language and Speech Tool for Italian; International Worksh Bernardo Magnini,Francesco Cutugno,Emanuele Pianta Confere

擦掉

Named Entity Recognition on Transcribed Broadcast News at EVALITA 2011oken broadcast news. In this paper, we present the training and test data used, the evaluation procedure and participants’ results. In particular, three participating systems are described and the results they obtained are discussed; special attention is given to the analysis of the impact of transcription errors on NER performance.

易受騙

convulsion

開(kāi)花期女

Bewertung der Untersuchungsergebnisse, from the target domain. The process was repeated a few times for building a new training resource partially adapted to the target domain. Using the new resource we trained three stacked parsers, and their combination was used to produce the final results.

freight

https://doi.org/10.1007/978-3-322-81698-6respond to sub-trees. A binary classifier, based on Maximum Entropy, is used to decide whether there is a coreference relationship between each pair of mentions detected in the previous phase. Clustering of entities is performed by a greedy clustering algorithm.

Concrete

https://doi.org/10.1007/978-3-658-03547-1 semantic categories, and it is an easier and more practical task with respect to WSD, that deals with very specific senses. We will report on the organization and results of the Evalita 2011 SuperSense Tagging task.

壓倒性勝利

ear-canal

NIL

書(shū)法