Задача 7

This paper describes the system used in Task-7 (Analysis of Clinical Text) of SemEval-2014 for detecting disorder men- tions and associating them with their re- lated CUI of UMLS1. For …...

We refined the performance of Co- coa/Peaberry, a linguistically moti- vated system, on extracting disease en- tities from clinical notes in the train- ing and development sets for Task 7. …...

We present our participation in Task 7 of SemEval shared task 2014. The goal of this particular task includes the identifica- tion of disorder named entities and the mapping of …...

This paper describes our participation on Task 7 of SemEval 2014, which fo- cused on the recognition and disambigua- tion of medical concepts. We used an adapted version of the …...

AbstractThis paper describes our submissions to task 7 in SemEval 2017, i.e., Detection and Interpretation of English Puns. We participated in the first two subtasks, which are to detect and …...

AbstractAutomatic extraction of semantic relations from text can support finding relevant information from scientific publications. We describe our participation in Task 7 of SemEval-2018 for which we experimented with two …...

AbstractNatural language processing (NLP) has been applied to various fields including text classification and sentiment analysis. In the shared task of assessing the funniness of edited news headlines, which is …...

AbstractThis paper presents the DuluthNLP submission to Task 7 of the SemEval 2021 competition on Detecting and Rating Humor and Offense. In it, we explain the approach used to train …...

AbstractThis paper presents one of the top winning solution systems for task 7 at SemEval2021, HaHackathon: Detecting and Rating Humor and Offense. This competition is divided into two tasks, task1 …...