Enhancing Anaphora Resolution for Czech
| Authors | |
|---|---|
| Year of publication | 2007 |
| Type | Article in Proceedings |
| Conference | RASLAN 2007 |
| MU Faculty or unit | |
| Citation | |
| Web | https://nlp.fi.muni.cz/raslan/2007/papers/4.pdf |
| Field | Use of computers, robotics and its application |
| Keywords | anaphora resolution; linguistic resources; verb valency; semantic plausibility; WordNet; Czech |
| Description | Resolution of anaphoric reference is one of the most important challenges in natural language processing (NLP). Functionality of most NLP systems crucially relies on an accurate mechanism for determining which expressions in the input refer to the same entity in the real world. The immense complexity of this issue has led the research community to adopt predominantly knowledge-poor methods, despite the fact that these are known to be incapable of solving this task reliably. This paper suggests several ways of extending such methods by further resources and mechanisms in order to arrive at a more adequate anaphora resolution procedure. First, the paper sketches how to exploit information about verb valencies or co-occurrence statistics to account for semantic plausibility of individual antecedent candidates. Further, several ways of adapting ML-based AR methods are suggested, so that they account for the structure of the AR task more closely. |
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