Joint Neural Entity Disambiguation with Output Space Search
Table 5: CoNLL 2003 Test-b
['[BOLD] Models', 'Heuristic', 'Depth ( [ITALIC] τ)', 'Beam Size (b)', 'In-KB acc %']
The results show that using a beam of size 5 improves upon single greedy search, and using heuristic h2 with flexible depth gives the best performance in terms of both prediction accuracy and efficiency (due to smaller search trees). When h1 is used, doubling the depth of the search tree brings about only a marginal improvement in accuracy at the cost of doubling the search depth and thus the prediction time.