Incorporating Relation Paths in Neural Relation Extraction
Table 2: P@N and F1 for relation extraction in texts containing different percentage of no-relation facts.
['Test Settings (Noise) P@N (%)', '75% 10%', '75% 20%', '75% 50%', '75% F1', '85% 10%', '85% 20%', '85% 50%', '85% F1', '95% 10%', '95% 20%', '95% 50%', '95% F1']
In the task of relation extraction, there are lots of noise in text which may hurt the model’s performance. More specifically, “No Relation” entity pair is a kind of noise, since “No Relation” could actually contain many unknown relation types, and thus might confuse the relation extraction systems. Therefore, it is important to verify the robustness of our model in the presence of massive noise. Here, we evaluate those models in three settings, with the same relational facts and different percentages of “No Relation” sentences in the testing sets.