Abstract
This notebook describes our participation to the Protest- New Lab, identifying protest events in news articles in English. Systems are challenged to perform unsupervised domain adaptation against three sub-tasks: document classification, sentence classification, and event ex- traction. We describe the final submitted systems for all sub-tasks, as well as a series of negative results. Results indicate pretty robust perfor- mances in all tasks (average F1 of 0.705 for the document classification sub-task, average F1 of 0.592 for the sentence classification sub-task; av- erage F1 0.528 for the event extraction sub-task), ranking in the top 4 systems, although drops in the out-of-domain test sets are not minimal.
| Original language | English |
|---|---|
| Title of host publication | Working Notes of CLEF 2019 |
| Subtitle of host publication | Conference and Labs of the Evaluation Forum |
| Publisher | CEUR Workshop Proceedings (CEUR-WS.org) |
| Pages | 1-13 |
| Number of pages | 14 |
| Volume | 2380 |
| Publication status | Published - 2019 |