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Thesis (Ph. D.)--University of Cambridge, 1993. / Cover title. "February 1993." Includes bibliographical references.

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Reference resolution is a major component of any natural language system. In the past 30 years significant progress has been made in coreference resolution. However, there is more anaphora in texts than coreference. I present a computational treatment of other-anaphora, i.e., referential noun phrases (NPs) with non-pronominal heads modi- fied by “other” or “another”: [. . . ] the move is designed to more accurately reflect the value of products and to put steel on more equal footing with other commodities. Such NPs are anaphoric (i.e., they cannot be interpreted in isolation), with an antecedent that may occur in the previous discourse or the speaker’s and hearer’s mutual knowledge. For instance, in the example above, the NP “other commodities” refers to a set of commodities excluding steel, and it can be paraphrased as “commodities other than steel”. Resolving such cases requires first identifying the correct antecedent(s) of the other-anaphors. This task is the major focus of this dissertation. Specifically, the dissertation achieves two goals. First, it describes a procedure by which antecedents of other-anaphors can be found, including constraints and preferences which narrow down the search. Second, it presents several symbolic, machine learning and hybrid resolution algorithms designed specifically for other-anaphora. All the algorithms have been implemented and tested on a corpus of examples from the Wall Street Journal. The major results of this research are the following: 1. Grammatical salience plays a lesser role in resolving other-anaphors than in resolving pronominal anaphora. Algorithms that solely rely on grammatical features achieved worse results than algorithms that used semantic features as well. 2. Semantic knowledge (such as “steel is a commodity”) is crucial in resolving other-anaphors. Algorithms that operate solely on semantic features outperformed those that operate on grammatical knowledge. 3. The quality and relevance of the semantic knowledge base is important to success. WordNet proved insufficient as a source of semantic information for resolving other-anaphora. Algorithms that use the Web as a knowledge base achieved better performance than those using WordNet, because the Web contains domain specific and general world knowledge which is not available from WordNet. 4. But semantic information by itself is not sufficient to resolve other-anaphors, as it seems to overgenerate, leading to many false positives. 5. Although semantic information is more useful than grammatical information, only integration of semantic and grammatical knowledge sources can handle the full range of phenomena. The best results were obtained from a combination of semantic and grammatical resources. 6. A probabilistic framework is best at handling the full spectrum of features, both because it does not require commitment as to the order in which the features should be applied, and because it allows features to be treated as preferences, rather than as absolute constraints. 7. A full resolution procedure for other-anaphora requires both a probabilistic model and a set of informed heuristics and back-off procedures. Such a hybrid system achieved the best results so far on other-anaphora.

Thesis (M.S.)--Massachusetts Institute of Technology, Dept. of Linguistics and Philosophy, 1981. / MICROFICHE COPY AVAILABLE IN ARCHIVES AND HUMANITIES. / Bibliography: leaves 54-55. / by Karuvannur Puthanveettil Mohanan. / M.S.

Thesis (M.A. (African Languages)) -- University of Limpopo, 2011 / This study evaluates the comparative analysis of cross-referencing in Northern Sotho monolingual dictionary and Northern Sotho-English bilingual dictionaries. The study argues that Northern Sotho-English Lexicographers do not treat cross-referencing in accordance with the lexicographic theories and principles. Since in this study cross-referencing is treated with regard to synonyms and antonyms only, the study has discovered that there are many problems in relation to the application of cross-referencing in these dictionaries. This enables dictionary users to follow it with ease, because if theories are not adhered to, then the motive for using dictionaries becomes null and void. The other thing is that lexicographers mix the translation equivalents of partial synonyms and complete synonyms, that is, partial synonyms are paired with complete synonyms, thus leading to orthorgraphic errors. Moreover, the study discovered that some emerging lexicographers are attempting to apply cross-referencing in their dictionaries, something which is a very good attempt. Therefore, the study recommends that major theories and principles of lexicography should be indicated in the front matter of the dictionaries. This will be to make sure that lexicographers themselves know about those theories, as that will make their dictionaries very useful to their readers.

Thesis (M.A.)--University of Hong Kong, 2001. / Includes bibliographical references (leaves 73-78).

Thesis (Ph. D.)--University of California, San Diego, 1985. / Vita. eContent provider-neutral record in process. Description based on print version record. Includes bibliographical references (leaves 255-259).

Thesis (M.A.)--University of Hong Kong, 2001. / Includes bibliographical references (leaves 73-78). Also available in print.

Thesis (Ph.D.)--University of Alberta, 2010. / Title from PDF file main screen (viewed on May 27, 2010). A thesis submitted to the Faculty of Graduate Studies and Research in partial fulfillment of the requirements for the degree of Doctor of Philosophy in Software Engineering and Intelligent Systems, Department of Electrical and Computer Engineering, University of Alberta. Includes bibliographical references.