Disambiguating Conjunctions in Named Entities
Paweł Mazur, Robert Dale · 2005
The recognition of named entities is now a welldeveloped area, with a range of symbolic and machine learning techniques that deliver high accuracy identification and categorisation of a variety of entity types. However, there are still some named entity phenomena that present problems for existing techniques; in particular, relatively little work has explored the disambiguation of conjunctions appearing in candidate named entity strings. We demonstrate that there are in fact four distinct uses of conjunctions in the context of named entities; we present the results of some experiments using machine-learned classifiers to disambiguate the dierent uses of the conjunction, with 81.73% of test examples being correctly classified. We provide some discussion and analysis of the problem of conjunction in named entities, and we show that there are some cases which are ambiguous even for humans.