NSURL-2019 Task 7: Named Entity Recognition (NER) in Farsi
This work addresses the problem of NER for Farsi language researchers by providing a benchmark, but it is incremental as it builds on existing NER methods.
The paper tackled Named Entity Recognition in Farsi by establishing a standard testbed and comparing approaches from six teams, with the best system achieving an F1 score of 85.4% on seven entity classes.
NSURL-2019 Task 7 focuses on Named Entity Recognition (NER) in Farsi. This task was chosen to compare different approaches to find phrases that specify Named Entities in Farsi texts, and to establish a standard testbed for future researches on this task in Farsi. This paper describes the process of making training and test data, a list of participating teams (6 teams), and evaluation results of their systems. The best system obtained 85.4% of F1 score based on phrase-level evaluation on seven classes of NEs including person, organization, location, date, time, money and percent.