The unification problem and several variants are presented. Various algorithms and data structures are discussed. Research on unification arising in several areas of computer science is surveyed, these areas include theorem proving, logic programming, and natural language processing. Sections of the paper include examples that highlight particular uses

This document is the user manual for FUF version 5.2, a natural language generator program that uses the technique of unification grammars. The program is composed of two main modules: a unifier and a linearizer. The unifier takes as input a semantic description of the text to be generated and a unification grammar, and produces as output a rich syntactic description of the text. The linearizer interprets this syntactic description and produces an English sentence. This manual includes a detailed presentation of the technique of unification grammars and a reference manual for the current implementation (FUF 5.2). Version 5.2 includes novel techniques in the unification allowing the specification of types and the expression of complete information. It also allows for procedural unification and supports sophisticated forms of control. Copyright © 1993 Michael Elhadad 1.

This paper introduces an efficient on-line parsing algorithm, and focuses on its practical application to natural language interfaces. The algorithm can be viewed as a generalized LR parsing algorithm that can handle arbitrary context-free grammars, including ambiguous grammars. Section 2 describes the algorithm by .extending the standard LR parsing algorithm with the idea of a "graph-structured stack". Section 3 describes how to represent parse trees efficiently, so that all possible parse trees (the parse forest) take at most polynomial space as the ambiguity of a sentence grows exponentially. In section 4, several examples are given. Section 5 presents several empirical results of the algorithm's practical performance, including comparison with Earley's algorithm. In section 6, we discuss how to enhance the algorithm to handle augmented context-free grammars rather than pure context-free grammars. Section 7 describes the concept of on-line parsing, taking advantage of left-to-right operation of our parsing algorithm. The on-line parser parses a sentence strictly from left to right, and starts parsing as soon as the user types in the first word, without waiting for the end of line. Benefits of on-line parsing are then discussed. Finally, several versions of on-line parser have been implemented, and they are mentioned in section 8

The thesis describes novel techniques and algorithms for the practical parsing of realistic Natural Language (NL) texts with a wide-coverage unification-based grammar of English. The thesis tackles two of the major problems in this area: firstly, the fact that parsing realistic inputs with such grammars can be computationally very expensive, and secondly, the observation that many analyses are often assigned to an input, only one of which usually forms the basis of the correct interpretation. The thesis starts by presenting a new unification algorithm, justifies why it is well-suited to practical NL parsing, and describes a bottom-up active chart parser which employs this unification algorithm together with several other novel processing and optimisation techniques. Empirical results demonstrate that an implementation of this parser has significantly better practical

this paper, we usually represent feature sets as graphs but the matrix notation will also be used occasionally. these graphs, the constituents of the rule are represented by labeled arcs, called attributes. The nodes in the graph are values. A value can be atomic or complex; a complex wdue is another set of attribute-value pairs. By convention, the symbol on the lefbhand side of a phrase structure rule is represented by the numeric attribute 0. Constituents on the right-hand side of the rule are numbered left-to-right, starting with 1. The above rule D PATR represents as the following feature set, shown here first as a graph and then as the equivalent matrix

Research in example-based machine translation (EBMT) has been hampered by the lack of efficient tree alignment algorithms for bilingual corpora. This paper describes an alignment algorithm for EBMT whose running time is quadratic in the size of the input parse trees. The algorithm uses dynamic programming to score all possible matching nodes between structure-sharing trees or forests. We describe the algorithm, various optimizations, and our implementation. 1 Introduction The development of a machine translation (MT) system requires the lengthy manual preparation of bilingual lexicons and transfer rules. Research over the past few years using parallel sentencealigned bilingual corpora suggests ways in which this manual effort can be partly replaced by corpus-based training. Some of this research has treated the sentences as unstructured word sequences to be aligned; this work has primarily involved the acquisition of bilingual lexical correspondences (Chen, 1993), although there has ...

this paper define the basic concepts of our formalism. Section 4 proves the soundness and completeness of our simplest parser, which is purely bottom-up and excludes rules with empty right-hand sides. Section 5 admits rules with empty right sides, and section 6 adds top-down filtering. Section 7 discusses the implementation and possible exten- sions

This paper presents a unification procedure which eliminates the redundant copying of structures by using a lay incremental copying approach to achieve structure sharing. Copying of structures accounts for a considerable amount of the total processing time. Several methods have been proposed to minimize the amount of necessaxy copying. Lazy Incremental Copying (LIC) is presented as a new solution to the copying problem. It synthesizes ideas of lazy copying with the notion of chronological dereferencing for achieving a high amount of structure sharing.

Gral)h Ullifi(:;xtion l'enlains the ntost (!Xl)eltSivc part of unification-bmed grammar parsing. Wc tion algorithms: avoidance of copying of unmodi fled sulgl'aphs. We propose a inethod of attaining such a design through a inethod of strm:turc-sharing which avoids log(d) overheads often associated with structm'c-sharilig of graphs without any us of costly ticpendency pointers. The proposed scheme elilninates r*:dundaut copying while maintaining the qu;sidestructive schcme's ability to aw)id over copying and early copying combined with its ability to handle cyclic structures without algorithmic additions.

Building on the well-established premise that reliable machine translation requires a significant degree of. text comprehension, this paper presents a recent advance in multi-lingual knowledgebased machine translation (KBMT). Unlike previous approaches, the current method provides for separate syntactic and semantic knowledge sources that are integrated dynamically for parsing and generation. Such a separation enables the system to have syntactic grammars, language specific but domain general, and semantic knowledge bases, domain specific but language general. Subsequently, grammars and domain knowledge are precompiled automatically in any desired combination to produce very efficient and very thorough real-time parsers. A pilot implementation of our KBMT architecture using functional grammars and entity-oriented semantics demonstrates the feasibility of the new approach? 1.