  In this empirical study, I compare various tree distance measures --
originally developed in computational biology for the purpose of tree
comparison -- for the purpose of parser evaluation. I will control for the
parser setting by comparing the automatically generated parse trees from the
state-of-the-art parser Charniak, 2000) with the gold-standard parse trees. The
article describes two different tree distance measures (RF and QD) along with
its variants (GRF and GQD) for the purpose of parser evaluation. The article
will argue that RF measure captures similar information as the standard EvalB
metric (Sekine and Collins, 1997) and the tree edit distance (Zhang and Shasha,
1989) applied by Tsarfaty et al. (2011). Finally, the article also provides
empirical evidence by reporting high correlations between the different tree
distances and EvalB metric's scores.

Computation and Language