In this paper, we report the results of our participation to the CLEF eHealth 2021 Task on “Multilingual Information Extraction". This year, this task focuses on Named Entity Recognition from Spanish clinical text in the domain of radiology reports. In particular, the main objective is to classify entities into seven different classes as well as hedge cues. Our main contribution can be summarized as follows: 1) continue the study of minimal/reproducible pipeline for text analysis baselines using a tidyverse approach in the R language; 2) evaluate the simplest memory based classifiers without optimization.
IMS-UNIPD @ CLEF eHealth Task 1: A memory based reproducible baseline
Di Nunzio G. M.
2021
Abstract
In this paper, we report the results of our participation to the CLEF eHealth 2021 Task on “Multilingual Information Extraction". This year, this task focuses on Named Entity Recognition from Spanish clinical text in the domain of radiology reports. In particular, the main objective is to classify entities into seven different classes as well as hedge cues. Our main contribution can be summarized as follows: 1) continue the study of minimal/reproducible pipeline for text analysis baselines using a tidyverse approach in the R language; 2) evaluate the simplest memory based classifiers without optimization.File in questo prodotto:
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