Preferences versus Adaptation during Referring Expression Generation
نویسندگان
چکیده
Current Referring Expression Generation algorithms rely on domain dependent preferences for both content selection and linguistic realization. We present two experiments showing that human speakers may opt for dispreferred properties and dispreferred modifier orderings when these were salient in a preceding interaction (without speakers being consciously aware of this). We discuss the impact of these findings for current generation algorithms.
منابع مشابه
Referring Expression Generation: Taking Speakers' Preferences into Account
We describe a classification-based approach to referring expression generation (REG) making use of standard context-related features, and an extension that adds speaker-related features. Results show that taking speakers’ preferences into account outperforms the standard REG model in four test corpora of definite descriptions.
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