.
Table 8. Model evaluation on row population task. Recall is the same for all methods because they share the same candidate generation module.
['# seed Method', '0 MAP', '0 Recall', '1 MAP', '1 Recall']
Results. The experiments are conducted under two settings: without any seed entity and with one seed entity. For experiments without the seed entity, we only use table caption for candidate generation. For entity ranking in EntiTables (zhang2017entitables), we use the combination of caption and label likelihood when there is no seed entity, and only use entity similarity when seed entities are available. This strategy works best on our validation set. In particular, previous methods rely on entity similarity and are not applicable or have poor results when there is no seed entity available. Our method achieves a decent performance even without any seed entity, which demonstrates the effectiveness of TURL for generating contextualized representations based on both table metadata and content.