A Type-coherent, Expressive Representation as an Initial Step to Language Understanding

A growing interest in tasks involving language understanding by the NLP community has led to the need for effective semantic parsing and inference. Modern NLP systems use semantic representations that do not quite fulfill the nuanced needs for language understanding: adequately modeling language semantics, enabling general inferences, and being accurately recoverable. This document describes underspecified logical forms (ULF) for Episodic Logic (EL), which is an initial form for a semantic representation that balances these needs. ULFs fully resolve the semantic type structure while leaving issues such as quantifier scope, word sense, and anaphora unresolved; they provide a starting point for further resolution into EL, and enable certain structural inferences without further resolution. This document also presents preliminary results of creating a hand-annotated corpus of ULFs for the purpose of training a precise ULF parser, showing a three-person pairwise interannotator agreement of 0.88 on confident annotations. We hypothesize that a divide-and-conquer approach to semantic parsing starting with derivation of ULFs will lead to semantic analyses that do justice to subtle aspects of linguistic meaning, and will enable construction of more accurate semantic parsers.Comment: Accepted for publication at The 13th International Conference on Computational Semantics (IWCS 2019

References to graphical objects in interactive multimodel queries

This thesis describes a computational model for interpreting natural language expressions in an interactive multimodal query system integrating both natural language text and graphic displays. The primary concern of the model is to interpret expressions that might involve graphical attributes, and expressions whose referents could be objects on the screen.Graphical objects on the screen are used to visualise entities in the application domain and their attributes (in short, domain entities and domain attributes). This is why graphical objects are treated as descriptions of those domain entities/attributes in the literature. However, graphical objects and their attributes are visible during the interaction, and are thus known by the participants of the interaction. Therefore, they themselves should be part of the mutual knowledge of the interaction.This poses some interesting problems in language processing. As part of the mutual knowledge, graphical attributes could be used in expressions, and graphical objects could be referred to by expressions. In consequence, there could be ambiguities about whether an attribute in an expression belongs to a graphical object or to a domain entity. There could also be ambiguities about whether the referent of an expression is a graphical object or a domain entity.The main contributions of this thesis consist of analysing the above ambiguities, de¬ signing, implementing and testing a computational model and a demonstration system for resolving these ambiguities. Firstly, a structure and corresponding terminology are set up, so these ambiguities can be clarified as ambiguities derived from referring to different databases, the screen or the application domain (source ambiguities). Secondly, a meaning representation language is designed which explicitly represents the information about which database an attribute/entity comes from. Several linguistic regularities inside and among referring expressions are described so that they can be used as heuristics in the ambiguity resolution. Thirdly, a computational model based on constraint satisfaction is constructed to resolve simultaneously some reference ambiguities and source ambiguities. Then, a demonstration system integrating natural language text and graphics is implemented, whose core is the computational model.This thesis ends with an evaluation of the computational model. It provides some concrete evidence about the advantages and disadvantages of the above approach

The use of world knowledge in resolving semantic ambiguities

This thesis report investigates a central problem to natural language processing, namely the problem of semantic ambiguity. The type of semantic ambiguities that are considered are those that are generally resolved by speakers of a given language by relying on common knowledge. Typical of this is the problem of pronoun resolution. In this report we investigate the thesis that the semantic theory of Richard Montague can be extended to accommodate the use of world knowledge. We propose an extension to Montague\u27s notion of contexts of use, and to the meaning representation. Meanings are represented as complex structures containing several features including the denotation. The method uses these structures to build contexts, and discourse structures that are then used in the dialogue to resolve certain types of ambiguities. Paper copy at Leddy Library: Theses & Major Papers - Basement, West Bldg. / Call Number: Thesis1991 .S222. Source: Masters Abstracts International, Volume: 31-01, page: 0352. Thesis (M.C.Sc.)--University of Windsor (Canada), 1991

Morphologically Complex Predicates in Japanese and What They Tell Us About Grammar Architecture

In this paper we take a fresh look at an old problem, the syntax and semantics of Japanese causatives. We demonstrate some seldom-noted similarities causatives bear to other Japanese morphologically complex predicates and argue why these similarities are important. Following a survey and critique of past analyses, we conclude that the principle of compositionality is at the root of the deficiencies of these analyses. We thus propose a modified, slightly non-compositional version of Manning et al.’s (1999) analysis, similar in spirit to Minimal Recursion Semantics (Copestake et al. 1995, 1999). We conclude with some discussion of possible replacements for compositionality