Sentence examples for meaning representation from inspiring English sources
TextOntoEx analyses natural domain text to extract candidate relations and then maps them into meaning representation to facilitate constructing ontology.
The Abstract Meaning Representation (AMR) is a representation for open-domain rich semantics, with potential use in fields like event extraction and machine translation.
The theory attempts to meet certain desiderata for a meaning representation, namely, the principles of adequacy, interpretability, uniformity, economy, and, in particular, cognitive correspondence.
Authors Petruck, M. R. L., & Dodge E. FrameNet (FN), Embodied Construction Grammar (ECG), and MetaNet (MN), are distinct from other linguistic resources since each relies on frame-based meaning representation, rather than logicsbased representation.
Its method of selecting among possible chains of inferences is consistent with the overall principle of "semantic preference" used to set up the original meaning representation, of which these anaphoric inference procedures are a manipulation.
To deal with the high degree of ambiguity present in this setting, we present a generative model that simultaneously segments the text into utterances and maps each utterance to a meaning representation grounded in the world state.
One particular model uses hyperedge replacement graph grammars to construct meaning representations.
It describes a grammar learning approach building Abstract Meaning Representations, a recently proposed, general formalism for representing core aspects of sentence meaning.
In this talk, I will present a framework that uses situated interactions to learn to map sentences to rich, logical meaning representations.
In her research she develops machine learning methods and computational models to gain a deeper understanding of the structure and dynamics of meaning representations both in language and in humans.
It is noteworthy that the conception of sentences as meaning representations echoes Montague's contention that language is logic.
