Automatic Semantic Tagging of Unknown Proper Names

Implemented methods for proper names recognition rely on large gazetteers of common proper nouns and a set of heuristic rules (e.g. Mr. as an indicator of a PERSON entity type). Though the performance of current PN recognizers is very high (over 90%), it is important to note that this problem is by no means a "solved problem". Existing systems perform extremely well on newswire corpora by virtue of the availability of large gazetteers and rule bases designed for specific tasks (e.g. recognition of Organization and Person entity types as specified in recent Message Understanding Conferences MUC). However, large gazetteers are not available for most languages and applications other than newswire texts and, in any case, proper nouns are an open class. In this paper we describe a context-based method to assign an entity type to unknown proper names (PNs). Like many others, our system relies on a gazetteer and a set of context-dependent heuristics to classify proper nouns. However, due to the unavailability of large gazetteers in Italian, over 20% detected PNs cannot be semantically tagged. The algorithm that we propose assigns an entity type to an unknown PN based on the analysis of syntactically and semantically similar contexts already seen in the application corpus. The performance of the algorithm is evaluated not only in terms of precision, fo l lowing the tradit ion of MUC conferences, but also in terms of Information Gain, an information theoretic measure that takes into account the complexity of the classification task. In troduc t ion In terms of syntactic categories, proper nouns are lexical NPs that can be formed by primitive proper names (Adol fo_Battaglia), groups of proper nouns of different semantic categories (San_Paolo di Brescia), and also of non-proper nouns (Banca dei regolamenti internazionali). In the latter case, capital letters are optional, making the problem of PN items identification even more complex. In the literature, it is accepted that an adequate treatment of proper nouns requires the use of a context-sensitive grammar (McDonald, 1996). McDonald points out that the context sensitivity requirement involves two complementary types of evidence: internal and external. The internal evidence, can be derived from the sequence of words in a text (proper nouns and trigger words, such as Inc., &, Ltd., Company, etc.), and is gained in almost all state-of-art PNs recognisers by the use of large gazetteers and lists of trigger words. The external evidence is the context of a proper noun, that provides classificatory criteria to reinforce internal evidence, if any, or supplies some classificatory evidence. In fact, proper names form an open class, making the incompleteness of gazetteers an obvious problem. The methods for recognition of proper nouns (PNs) described in literature closely reflects this view of the problem. PN identification typically includes: • a gazetteer lookup, which locates simple and complex nominals identifying common PNs, such as companies, person names, locations, etc. • a set of patterns or rules, stated in terms of part-of-speech, syntactic or lexical features (e.g. Mr. as an indicator of a PERSON entity type), orthographic features (e.g. capitalization), etc.