Year of publication
- Textanalyse ; Linguistische Datenverarbeitung; Computerlinguistik (9)
- Computerlinguistik (6)
- Textanalyse (4)
- Linguistische Datenverarbeitung (3)
- Linguistische Datenverarbeitung (2)
- Textanalyse (2)
- Linguistische Datenverarbeitung (1)
- Textanalyse ; Linguistische Datenverarbeitung ; Computerlinguistik (1)
- Können Computer Texte verstehen? Maschinelle Sprachverarbeitung aus den Perspektiven von Philosophischer Hermeneutik, Kognitionswissenschaften und Künstlicher Intelligenz (1999)
- Vortragsfolien: Vortragsreihe "Unplugged Heads", Institut für Neue Medien, Frankfurt am Main, 11. Mai 1999.
- Die "Message Understanding"-Konferenzen - eine Institution zur Förderung der Entwicklung anwendungstauglicher inhaltserschließender Textanalysesysteme (1998)
- Vortragsfolien: eingeladener Vortrag, inm - numerical magic Gesellschaft für neue medien mbH, Frankfurt am Main, 8. Mai 1998
- Three Algorithms for Competence-Oriented Anaphor Resolution (2004)
- In the last decade, much effort went into the design of robust third-person pronominal anaphor resolution algorithms. Typical approaches are reported to achieve an accuracy of 60-85%. Recent research addresses the question of how to deal with the remaining difficult-toresolve anaphors. Lappin (2004) proposes a sequenced model of anaphor resolution according to which a cascade of processing modules employing knowledge and inferencing techniques of increasing complexity should be applied. The individual modules should only deal with and, hence, recognize the subset of anaphors for which they are competent. It will be shown that the problem of focusing on the competence cases is equivalent to the problem of giving precision precedence over recall. Three systems for high precision robust knowledge-poor anaphor resolution will be designed and compared: a ruleset-based approach, a salience threshold approach, and a machine-learning-based approach. According to corpus-based evaluation, there is no unique best approach. Which approach scores highest depends upon type of pronominal anaphor as well as upon text genre.
- A Machine Learning Approach to Preference Strategies for Anaphor Resolution (2005)
- In the last years, much effort went into the design of robust anaphor resolution algorithms. Many algorithms are based on antecedent filtering and preference strategies that are manually designed. Along a different line of research, corpus-based approaches have been investigated that employ machine-learning techniques for deriving strategies automatically. Since the knowledge-engineering effort for designing and optimizing the strategies is reduced, the latter approaches are considered particularly attractive. Since, however, the hand-coding of robust antecedent filtering strategies such as syntactic disjoint reference and agreement in person, number, and gender constitutes a once-for-all effort, the question arises whether at all they should be derived automatically. In this paper, it is investigated what might be gained by combining the best of two worlds: designing the universally valid antecedent filtering strategies manually, in a once-for-all fashion, and deriving the (potentially genre-specific) antecedent selection strategies automatically by applying machine-learning techniques. An anaphor resolution system ROSANA-ML, which follows this paradigm, is designed and implemented. Through a series of formal evaluations, it is shown that, while exhibiting additional advantages, ROSANAML reaches a performance level that compares with the performance of its manually designed ancestor ROSANA.
- Robuste Anaphernresolution (2004)
- Towards Best Practice Standards for Enhanced Knowledge Discovery Systems (2004)
- Assessing enhanced knowledge discovery systems (eKDSs) constitutes an intricate issue that is understood merely to a certain extent by now. Based upon an analysis of why it is difficult to formally evaluate eKDSs, it is argued for a change of perspective: eKDSs should be understood as intelligent tools for qualitative analysis that support, rather than substitute, the user in the exploration of the data; a qualitative gap will be identified as the main reason why the evaluation of enhanced knowledge discovery systems is difficult. In order to deal with this problem, the construction of a best practice model for eKDSs is advocated. Based on a brief recapitulation of similar work on spoken language dialogue systems, first steps towards achieving this goal are performed, and directions of future research are outlined.
- Anaphor resolution and the scope of syntactic constraints (1996)
- An anaphor resolution algorithm is presented which relies on a combination of strategies for narrowing down and selecting from antecedent sets for re exive pronouns, nonre exive pronouns, and common nouns. The work focuses on syntactic restrictions which are derived from Chomsky's Binding Theory. It is discussed how these constraints can be incorporated adequately in an anaphor resolution algorithm. Moreover, by showing that pragmatic inferences may be necessary, the limits of syntactic restrictions are elucidated.
- Resolving anaphoric references on deficient syntactic descriptions (1997)
- Syntactic coindexing restrictions are by now known to be of central importance to practical anaphor resolution approaches. Since, in particular due to structural ambiguity, the assumption of the availability of a unique syntactic reading proves to be unrealistic, robust anaphor resolution relies on techniques to overcome this deficiency. In this paper, two approaches are presented which generalize the verification of coindexing constraints to de cient descriptions. At first, a partly heuristic method is described, which has been implemented. Secondly, a provable complete method is specified. It provides the means to exploit the results of anaphor resolution for a further structural disambiguation. By rendering possible a parallel processing model, this method exhibits, in a general sense, a higher degree of robustness. As a practically optimal solution, a combination of the two approaches is suggested.
- Coreference-Based Summarization and Question Answering: a Case for High Precision Anaphor Resolution (2003)
- Approaches to Text Summarization and Question Answering are known to benefit from the availability of coreference information. Based on an analysis of its contributions, a more detailed look at coreference processing for these applications will be proposed: it should be considered as a task of anaphor resolution rather than coreference resolution. It will be further argued that high precision approaches to anaphor resolution optimally match the specific requirements. Three such approaches will be described and empirically evaluated, and the implications for Text Summarization and Question Answering will be discussed.