A Multi-task Approach for Named Entity Recognition in Social Media Data
Table 2: This table shows the final results of our submission. The hardest class to predict for is creative-work, while the easiest is person.
['[BOLD] Classes', '[BOLD] Precision (%)', '[BOLD] Recall (%)', '[BOLD] F1 (%)']
Our approach obtains the best results for the person and location categories. It is less effective for corporation, and the most difficult categories for our system are creative-work and product. Our intuition is that the latter two classes are the most difficult to predict for because they grow faster and have less restrictive patterns than the rest. For instance, products can have any type of letters or numbers in their names, or in the case of creative works, as many words as their titles can hold (e.g. name of movies, books, songs, etc.).