Разрешение неоднозначности

We present a cost-based (or energy-based) model of dis- ambiguation. When a sentence is ambiguous, a parse with the least cost is chosen from among multiple hypotheses. Each hypothesis is …...

In natural language processing, ambiguity res- olution is a central issue, and can be regarded as a preference assignment problem. In this paper, a Generalized Probabilistic Semantic Model (GPSM) is …...

The Slot Grammar system is interesting for natural language applica- tions because it can deliver parses with deep grammatical information on a reasonably broad scale. The paper describes a numerical …...

Many current approaches to statistical lan- guage modeling rely on independence a.~- sumptions 1)etween the different explana- tory variables. This results in models which are computationally simple, but which only …...

AbstractIn this paper we describe and experimentally evaluate FromTo K/E, a rule-based Korean-English machine translation system adapting transfer methodology. In accordance with the view that a successful Korean-English machine translation …...

We describe a methodology for learning a disambiguation model for deep pragmatic interpretations in the context of situated task-oriented dialogue. The system accu- mulates training examples for ambiguity resolution by …...

AbstractIn open-domain question answering, questions are highly likely to be ambiguous because users may not know the scope of relevant topics when formulating them. Therefore, a system needs to find …...

AbstractNatural language is ambiguous. Resolving ambiguous questions is key to successfully answering them. Focusing on questions about images, we create a dataset of ambiguous examples. We annotate these, grouping answers …...