Unsupervised Latent Tree Induction with Deep Inside-Outside Recursive Autoencoders
Table 5: P@1, P@10, and P@100 for labeled chunks from CoNLL-2000 and CoNLL 2012 datasets. For all metrics, higher is better. The top value in each column is bolded. Diora uses the concatenation of the inside and outside vector at each cell which performed better than either in isolation.
['[BOLD] Model', 'Dim', '[BOLD] CoNLL 2000 P@1', '[BOLD] CoNLL 2000 P@10', '[BOLD] CoNLL 2000 P@100', '[BOLD] CoNLL 2012 P@1', '[BOLD] CoNLL 2012 P@10', '[BOLD] CoNLL 2012 P@100']
For each of the labeled spans with length greater than one, we first generate its phrase representation. We then calculate its cosine similarity to all other labeled spans. We then calculate if the label for that query span matches the labels for each of the K most similar other spans in the dataset.