More precisely, a labeled corpus for entity type classification consists of a set of extracted entity mentions {m i } N i=1 (i.e., token spans representing entities in text), the context (e.g., sentence, paragraph) of each mention {c i } N i=1 , and the candidate type sets {Y i } N i=1 automatically generated for each mention.
we compute a probability distribution over all the K = |Y| types in the target type hierarchy Y.