Managing Lexical Ambiguity in the Generation of Referring Expressions
نویسندگان
چکیده
منابع مشابه
Generation of Referring Expressions: Managing Structural Ambiguities
Existing algorithms for the Generation of Referring Expressions tend to generate distinguishing descriptions at the semantic level, disregarding the ways in which surface issues can affect their quality. This paper considers how these algorithms should deal with surface ambiguity, focussing on structural ambiguity. We propose that not all ambiguity is worth avoiding, and suggest some ways forwa...
متن کاملCorpus-based Referring Expressions Generation
In Natural Language Generation, the task of attribute selection (AS) consists of determining the appropriate attribute-value pairs (or semantic properties) that represent the contents of a referring expression. Existing work on AS includes a wide range of algorithmic solutions to the problem, but the recent availability of corpora annotated with referring expressions data suggests that corpus-b...
متن کاملLexical Choice and Conceptual Perspective in the Generation of Plural Referring Expressions
A fundamental part of the process of referring to an entity is to categorise it (for instance, as the woman). Where multiple categorisations exist, this implicitly involves the adoption of a conceptual perspective. A challenge for the automatic Generation of Referring Expressions is to identify a set of referents coherently, adopting the same conceptual perspective. We describe and evaluate an ...
متن کاملSpecifying Generation of Referring Expressions by Example
A module for generation of referring expressions (GRE) derives descriptions that identify specified entities in context. In the implemented system I describe here for specifying simple cases of GRE by example, system-builders pair entities with descriptions of them that would be satisfactory for a system to use in context. Automatic methods then construct a suitable knowledge base and context s...
متن کاملCorpus-based evaluation of Referring Expressions Generation
Corpus-based evaluation of NLP systems has become a dominant methodology. Typically, some metric is invoked to evaluate the results produced by a system against a ‘gold standard’ represented in the corpus. Despite growing recognition of the importance of empirical evaluation in NLG, resources and methodologies for evaluation of Generation of Referring Expressions (GRE) are in their infancy (but...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: International Journal of Intelligent Systems and Applications
سال: 2013
ISSN: 2074-904X,2074-9058
DOI: 10.5815/ijisa.2013.08.04