Daniel Bauer

VigNet: Grounding Language in Graphics using Frame Semantics

This paper introduces Vignette Semantics, a lexical semantic theory based on Frame Semantics that represents conceptual and graphical relations. We also describe a lexical resource that implements this theory, VigNet, and its application in text-to-scene generation.

The Dependency-Parsed FrameNet Corpus

When training semantic role labeling systems, the syntax of example sentences is of particular importance. Unfortunately, for the FrameNet annotated sentences, there is no standard parsed version. The integration of the automatic parse of an annotated sentence with its semantic annotation, while conceptually straightforward, is complex in practice. We present a standard dataset that is publicly available and that can be used in future research. This dataset contains parser-generated dependency structures (with POS tags and lemmas) for all FrameNet 1.5 sentences, with nodes automatically associated with FrameNet annotations.

Annotation Tools and Knowledge Representation for a Text-To-Scene System

Text-to-scene conversion requires knowledge about how actions and locations are expressed in language and realized in the world. To provide this knowlege, we are creating a lexical resource (VigNet) that extends FrameNet by creating a set of intermediate frames (vignettes) that bridge between the high-level semantics of FrameNet frames and a new set of low-level primitive graphical frames. Vignettes can be thought of as a link between function and form ‐ between what a scene means and what it looks like. In this paper, we describe the set of primitive graphical frames and the functional properties of 3D objects (affordances) we use in this decomposition. We examine the methods and tools we have developed to populate VigNet with a large number of action and location vignettes.

Collecting Spatial Information for Locations in a Text-to-Scene Conversion System

We investigate using Amazon Mechanical Turk (AMT) for building a low-level description corpus and populating VigNet, a comprehensive semantic resource that we will use in a text-to-scene generation system. To depict a picture of a location, VigNet should contain the knowledge about the typical objects in that location and the arrangements of those objects. Such information is mostly common-sense knowledge that is taken for granted by human beings and is not stated in existing lexical resources and in text corpora. In this paper we focus on collecting objects of locations using AMT. Our results show that it is a promising approach.

Photochemistry of 2,3-dimethylcyclobutanone. Temperature and wavelength effects.

Abstract The ratio of products formed in the photochemistry of cis- and trans-2,3-dimethyl-cyclobutanone in alcohols is found to be wavelength and temperature dependent.

Increasing Coverage of Syntactic Subcategorization Patterns in FrameNet Using Verbnet

We analyze the extent to which lexicographic annotations in FrameNet exemplify syntactic sub categorization patterns in corpora and present a method based on Verb net to decrease syntactic coverage gaps for most defined lexical units in FrameNet by 98% with high precision. The expanded set of annotated example sentences comprises about three times as many example sentences than those provided by FrameNet.

Documenting Endangered Languages with the WordsEye Linguistics Tool

In this paper, we describe how field linguists can use the WordsEye Linguistics Tool (WELT) to study endangered languages. WELT is a tool under development for eliciting endangered language data and formally documenting a language, based on WordsEye (Coyne and Sproat, 2001), a text-to-scene generation tool that produces 3D scenes from text input. First, a linguist uses WELT to create elicitation materials and collect language data. Next, he or she uses WELT to formally document the language. Finally, the formal models are used to create a textto-scene system that takes input in the endangered language and generates a picture representing its meaning.

Grammar-Based Semantic Parsing Into Graph Representations

Grammar-Based Semantic Parsing Into Graph Representations

Using Frame Semantics in Natural Language Processing

We summarize our experience using FrameNet in two rather different projects in natural language processing (NLP). We conclude that NLP can benefit from FrameNet in different ways, but we sketch some problems that need to be overcome.