Input: Topic/Focus Articulation And Intensional Logic A semantic analysis of topic and focus as two parts of tectograamatical representation by means of transparent intensional logic (TIL) ia presented. It is pointed out that two sentences (more precisely, their tectograamatical representations) differing just in the topic/focus articulation (TFA) denote different propositions, i. e. that TFA has an effect upon the semantic content of the sentence. An inforaal short description of an algorithm handling the TFA in the translation of tectogrammatical representations into the constructions of TIL is added. The TFA algorithm divides a representation into two parts corresponding to the topic and focus; every part is analyzed (translated) in isolation and then the resulting construction is put together. The TIL construction discussed here

Topic

Focus

Logic

semantic analysis

analysis

topic

focus

parts

representation

logic

sentences

representations

topic

focus

effect

semantic

content

sentence

description

algorithm

translation

representations

constructions

algorithm

representation

parts

topic

focus

part

translated

isolation

resulting

construction

construction

semantic analysis

topic

description

algorithm

content

sentence


Input: Bilingual Generation Of Weather Forecasts In An Operations Environment In 1986 the first experiments in text generation applied to weather forecasts resulted in a prototype system (RAREAS [6, 3]) for producing English marine bulletins from forecast data. Subsequent work in 1987 added French output to make the initial system bilingual (RAREAS-2 [llj). During 1988-1989 a full-scale operational system was created to meet the needs of daily marine forecast production for three regional centres in the Canadian Atmospheric Environment Service

Generation

Environment

experiments

text generation

applied

resulted

prototype

system

English

data

output

system

full-scale

system

Environment

experiments

system


Input: Syllable-Based Morphology This paper presents a language for the description of morphological alternations which is based on syllable structure. The justification for such an approach is discussed with reference to examples from a variety of languages and the approach is compared to Koskenniemi' s two-level account of morphonoiogy. Keywords: morphology, phonology, syllables.

Based

Morphology

paper

language

description

alternations

based

structure

justification

approach

reference

examples

variety

languages

approach

two-level

morphology

phonology

paper

language


Input: Knowledge Acquisition And Chinese Parsing Based On Corpus In Natural Language Processing (NLP), one key problem is how to design a robust and effective parsing system. In this paper, we will introduce a corpus based Chinese parsing system. Our efforts arc concctrated on: (1) knowledge acquisition and representation; and (2) the parsing scheme. The knowledge of this system is principally extracted from analyzed corpus, others are a few grammatical principles, i. e. the four axioms of the Dependency Grammar (DG). In addition, we also propose the fifth axiom of DG to support the parsing of Chinese sentences.

Knowledge

Acquisition

Chinese

Parsing

Based

Corpus

Natural Language Processing

problem

design

robust

parsing

system

paper

corpus

based

Chinese

parsing

system

efforts

arc

knowledge

acquisition

representation

parsing

scheme

knowledge

system

extracted

corpus

principles

axioms

Dependency Grammar

addition

propose

axiom

support

parsing

Chinese

sentences

Corpus

Parsing

parsing

sentences

paper

system

knowledge

corpus


Input: Automatic Model Refinement-With An Application To Tagging Statistical NLP models usually only consider coarse information and very restricted context to make the estimation of parameters feasible. To reduce the modeling error introduced by a simplified probabilistic model, the Classification and Regression Tree (CART) method was adopted in this paper to select more discriminative features for automatic model refinement. Because the features are adopted dependently during splitting the classification tree in CART, the number of training data in each terminal node is small, which makes the labeling process of terminal nodes not robust. This over-tuning phenomenon cannot be completely removed by cross-validation process (i. e., pruning process). A probabilistic classification model based on the selected discriminative features is thus proposed to use the training data more efficiently. In tagging the Brown Corpus, our probabilistic classification model reduces the error rate of the top 10 error dominant words from 5. 71% to 4. 35%, which shows 23. 82% improvement over the unrefined model.

Automatic

Model

Refinement

Application

Tagging

Statistical

models

information

context

estimation

parameters

modeling

error

probabilistic model

model

Classification

Regression

Tree

method

paper

features

automatic

model

refinement

features

splitting

classification

tree

number

training

data

terminal

node

process

terminal

nodes

robust

phenomenon

cross-validation

process

process

classification model

model

based

features

proposed

training

data

tagging

Brown Corpus

Corpus

classification model

model

error rate

rate

error

words

improvement

model

probabilistic model

error

classification model

error rate

paper

method

features

refinement

features

classification model

tagging

Brown Corpus


Input: Generating Multilingual Documents From A Knowledge Base The TECHDOC Project TECHDOC is an implemented system demonstrating the feasibility of generating multilingu. il technical documents on the basis of a language-independent knowledge base. Its application domain is use]-and maintenance instructions, which are produced from underlying plan structures representing the activities, the participating objects with their properties, relations, and so on. This paper gives a brief outline of the system architecture and discusses some recent developments in the project: the addition of actual event simulation in the KM, steps towards a document authoring tool, and a multimodal user interface.

Generating

Documents

Knowledge Base

Base

Project

implemented

system

generating

documents

basis

language-independent

knowledge base

base

application

domain

maintenance

instructions

structures

objects

properties

relations

paper

outline

system architecture

architecture

developments

project

addition

event

simulation

steps

document

tool

user interface

Documents

Knowledge Base

documents

knowledge base

paper

system architecture


Input: A Reestimation Algorithm For Probabilistic Ttecursive Transition Network Probabilistic. Recursive Transition Network (I' KTN) is an elevated version of RTN to model and process languages in stochastic, parameters. The representation is a direct derivation from the KTN and keeps much the spirit of Hidden Markov Model at the same time. We present a reestimation algorithm for PHTN that is a variation of Inside Outside algorithm that computes the values of the probabilistic parameters from sample sentences (parsed or uuparsed).

Algorithm

Transition

Network

Transition

Network

version

model

process

languages

parameters

representation

derivation

Hidden Markov Model

time

algorithm

variation

algorithm

computes

parameters

sample

sentences

Algorithm

Network

Network

languages


Input: DCKR-Knowledge Representation In Prolog And Its Application To Natural Language Processing " important tasks for natural language processing. Basin to semantic processing is descriptions of lexical items. The most frequently used form of description of lexical items is probably Frames or Objects. Therefore in what form Frames or Objects are expressed is a key issue for natural language processing. A method of the Object representation in Prolog called DCKR will be introduced. It will be seen that if part of general knowledge and a dictionary are described in DCKR, part of context-processing and the greater part of semantic processing can be left to the functions built in Prolog. 09) se (animal, age: X, _):-bottomof (S, B), sem (B, birthYear: Y, _), X is 1986-Y. 10) seni (face, P, S):-hasa (eye, P, [face I S]); hasa (nose, P, [face IS]); has a (mou th, P, [face! S]). Now the meanings of the gem, isa and hasa predicates, which are important to descriptions in DCKR, are explained later using the DCKR examples given above. 1. I n troduct i on Relationships between knowledge represented predicate logic formulas and knowledge represented Frames or Siruciured objects are clarified by [Hayes 80], [Nilsson 80], CGoebel 85], [Bowen 85], al, but their methods requires separately interpreter for their representation. et an The authors have developed a knowledge representation form called DCKR (Definite Clause Knowledge Representation) [Koyama 85]. In DCKR, each of the sip_ts composing of a Structured Object (hereinafter simply called an object) is represented by a Horn clause (a Prolog statement) with the " " sen " " predicate (to be explained in Section 2) as its head. Therefore, an Object can be regarded as a set of Horn clauses (slots) headed by the sen predicate with the same first argument. From the foregoing it follows that almost all of a program for performing semantic intepretations relative to lexical items described in DCKR can be replaced by functions built in Prolog. That is, most of programming efforts of semantic processing can be left to the functions built in Pro 1og. DCKR will be described in detail in Section 2. Section 3 will discuss applications of DCKR to semantic processing of natural languages. "

Knowledge Representation

Application

Natural Language Processing

tasks

natural language processing

semantic

processing

descriptions

lexical items

items

form

description

lexical items

items

form

issue

natural language processing

method

Object

representation

called

part

knowledge

dictionary

part

context-processing

part

semantic

processing

functions

animal

descriptions

examples

knowledge

logic

formulas

knowledge

objects

methods

requires

interpreter

representation

developed

knowledge representation

form

called

Clause

Knowledge Representation

Object

called

object

clause

sen

Section

Object

clauses

sen

argument

program

performing

semantic

relative

lexical items

functions

programming

efforts

semantic

processing

functions

detail

Section

Section

applications

semantic

processing

natural languages

descriptions

lexical items

description

lexical items

Section

applications


Input: Improving Search Strategies An Experiment In Best-First Parsing " Viewing the syntactic analysis of natural language as a search problem, the right choice of parsing strategy plays an important role in the performance of natural language parsers. After a motivation of the use of various heuristic criteria, a framework for defining and testing' parsing strategies is presented. On this basis systematic tests on different parsing strategies have been performed, the results of which are dicussed. Generally; hese tests show that a " " guided " " depth-oriented strategy gives a considerable reduction of search effort compared to the classical depth first strategy. "

Search Strategies

Experiment

Parsing

syntactic analysis

natural language

search

problem

choice

parsing

strategy

role

performance

natural language

parsers

motivation

criteria

framework

testing

parsing

strategies

basis

tests

parsing

strategies

performed

results

tests

strategy

reduction

search

effort

strategy

strategy

performance

tests

strategies


Input: Generating Multimodal Output-Conditions, Advantages And Problems " In natural communication situations, multimodal referent specification is frequent and efficient. The linguistic component are deictic expressions, e. g.' this' and' here'. Extralinguistic devices in dialogs are different body movements, mainly pointing gestures. Their functional equivalent in texts are means like arrows and indices. This paper has two intentions. First, it discusses the advantages of multimodal reference in interhuman communication which motivate the integration of extralinguistic " " pointing " " devices into NL dialog systems. The generation of multimodal output poses specific problems, which have no counterpart in the analysis of multimodal input. The second part presents the strategy for generating multimodal output which has been developed within the framework of the XTRA system (a NL access system to expert systems). XTRA allows the combination of verbal descriptions and pointing gestures in order to specify elements of the given visual context, i. e. a form displayed on the screen. The component POPEL generates referential expressions which may be accompanied by a pointing gesture. The appearance of these gestures depends on several factors, e. g. the type of referent (whether it is a region or an entry of the form) and its complexity. "

Generating

Output-

Problems

natural

communication

situations

referent

specification

component

expressions

devices

dialogs

gestures

texts

indices

paper

advantages

reference

communication

integration

devices

dialog systems

generation

output

problems

analysis

input

part

strategy

generating

output

developed

framework

system

access

system

expert systems

combination

verbal

descriptions

gestures

order

context

form

displayed

screen

component

generates

expressions

gesture

gestures

factors

type

referent

region

entry

form

complexity

generation

output

generating

output

component

expressions

analysis

input

part

strategy

factors

gestures


Input: Generalizing Local and Non-Local Word-Reordering Patterns for Syntax-Based Machine Translation Syntactic word reordering is essential for translations across different grammar structures between syntactically distant language-pairs. In this paper, we propose to embed local and non-local word reordering decisions in a synchronous context free grammar, and leverages the grammar in a chart-based decoder. Local word-reordering is effectively encoded in Hiero-like rules; whereas non-local word-reordering, which allows for long-range movements of syntactic chunks, is represented in tree-based reordering rules, which contain variables correspond to source-side syntactic constituents. We demonstrate how these rules are learned from parallel corpora. Our proposed shallow Tree-to-String rules show significant improvements in translation quality across different test sets.

Word-

Patterns

Syntax-

Based

Machine Translation

Syntactic

word

translations

structures

language-pairs

paper

propose

word

decisions

synchronous context free grammar

leverages

decoder

word-reordering

rules

word-reordering

syntactic

chunks

tree-based

rules

variables

source-side

syntactic

constituents

rules

parallel corpora

corpora

proposed

Tree-to-

String

rules

improvements

translation quality

quality

test sets

rules

word-reordering

rules

parallel corpora


Input: Automatic Acquisition of Basic Katakana Lexicon from a Given Corpus Abstract.

Automatic

Acquisition

Basic

Lexicon

Corpus

Abstract

Lexicon

Corpus


Input: A Twin-Candidate Model of Coreference Resolution with Non-Anaphor Identification Capability Abstract.

Candidate

Model

Coreference Resolution

Resolution

Identification

Capability

Abstract

Model

Coreference Resolution


Input: The Influence of Data Homogeneity on NLP System Performance In this work we study the influence of corpus homogeneity on corpus-based NLP system performance. Experiments are performed on both stochastic language models and an EBMT system translating from Japanese to English with a large bicorpus, in order to reassess the assumption that using only homogeneous data tends to make system performance go up. We describe a method to represent corpus homogeneity as a distribution of similarity coefficients based on a cross-entropic measure investigated in previous works. We show that beyond minimal sizes of training data the excessive elimination of heterogeneous data proves prejudicial in terms of both perplexity and translation quality: excessively restricting the training data to a particular domain may be prejudicial in terms of In-Domain system performance, and that heterogeneous, Out-of-Domain data may in fact contribute to better sytem performance.

Influence

Data

Homogeneity

NLP System

Performance

study

influence

corpus

homogeneity

corpus-based

NLP system

performance

Experiments

performed

language models

models

system

translating

Japanese

English

order

assumption

data

system

performance

method

corpus

homogeneity

distribution

similarity

coefficients

based

cross-entropic

sizes

training

data

elimination

data

terms

perplexity

translation quality

training

data

domain

terms

Domain

system

performance

Domain

data

performance

Homogeneity

Performance

homogeneity

performance

Domain

performance

Experiments

language models

translating

Japanese

sizes

data


Input: Using Maximum Entropy to Extract Biomedical Named Entities without Dictionaries Current NER approaches include: dictionary-based, rule-based, or machine learning. Since there is no consolidated nomenclature for most biomedical NEs, most NER systems relying on limited dictionaries or rules do not perform satisfactorily. In this paper, we apply Maximum Entropy (ME) to construct our NER framework. We represent shallow linguistic information as linguistic features in our ME model. On the GENIA 3. 02 corpus, our system achieves satisfactory F-scores of 74. 3% in protein and 70. 0% overall without using any dictionary. Our system performs significantly better than dictionary-based systems. Using partial match criteria, our system achieves an F-score of 81. 3%. Using appropriate domain knowledge to modify the boundaries, our system has the potential to achieve an F-score of over 80%.

Maximum Entropy

Extract

Named

Current

approaches

include

dictionary-based

rule-based

machine learning

systems

dictionaries

rules

perform

paper

apply

Maximum Entropy

Entropy

construct

framework

linguistic information

linguistic features

model

corpus

system

protein

dictionary

system

performs

dictionary-based

dictionary-based systems

systems

partial

match

criteria

system

domain knowledge

boundaries

system

dictionaries

systems

Maximum Entropy

framework

system

dictionary-based systems


Input: Resolving Pronominal References in Chinese with the Hobbs Algorithm " This study addresses pronominal anaphora resolution, including zero pronouns, in Chinese. A syntactic, rule-based pronoun resolution algorithm, the " " Hobbs algorithm " " was run on " " gold standard " " hand parses from the Penn Chinese Treebank. While first proposed for English, the algorithm counts for its success on two characteristics that Chinese and English have in common. Both languages are SVO, and both are fixed word order languages. No changes were made to adapt the algorithm to Chinese. The accuracy of the algorithm on overt, third-person pronouns at the matrix level was 77. 6%, and the accuracy for resolving matrix-level zero pronouns was 73. 3%. In contrast, the accuracy of the algorithm on pronouns that appeared in subordinate constructions was only 43. 3%, providing support for Miltsakaki' s two-mechanism proposal for resolving inter-vs. "

Chinese

Algorithm

study

anaphora resolution

resolution

including

Chinese

syntactic

rule-based

resolution

algorithm

algorithm

gold standard

standard

hand

parses

Chinese

proposed

English

algorithm

success

characteristics

Chinese

English

common

languages

word

order

languages

adapt

algorithm

Chinese

accuracy

algorithm

matrix

level

accuracy

matrix-level

contrast

accuracy

algorithm

constructions

providing

support

two-mechanism

proposal

study

anaphora resolution

algorithm

gold standard

characteristics

algorithm

order

languages

algorithm

accuracy

algorithm

accuracy


Input: Chinese Word Segmentation Based On Direct Maximum Entropy Model Och, Franz Josef; Ney, Hermann, Discriminative Training And Maximum Entropy Models For Statistical Machine Translation, Annual Meeting Of The Association For Computation al Linguistics, 2002 * * * Gao, Jianfeng; Li, Mu; Huang, Changning, Improved Source-Channel Models For Chinese Word Segmentation, Annual Meeting Of The Association For Computation al Linguistics, 2003

Chinese Word Segmentation

Word Segmentation

Based

Maximum Entropy Model

Entropy

Model

Training

Maximum Entropy

Entropy

Models

Statistical Machine Translation

Machine Translation

Association

Computation

Linguistics

Source-

Channel

Models

Chinese Word Segmentation

Word Segmentation

Association

Computation

Linguistics

Maximum Entropy Model

Chinese Word Segmentation

Maximum Entropy

Statistical Machine Translation

Models

Chinese Word Segmentation


Input: Linguistic Variation And Computation (Invited Talk) Language variationists study how languages vary along geographical or social lines or along lines of age and gender. Variationist data is available and challenging, in particular for dialectology, the study of geographical variation, which will be the focus of this paper, although we present approaches we expect to transfer smoothly to the study of variation correlating with other extralinguistic variables. Techniques from computational linguistics on the one hand, and standard statistical data reduction techniques on the other, not only shed light on this classic linguistic problem, but they also suggest avenues for exploring the question at more abstract levels, and perhaps for seeking the determinants of variation.

Variation

Computation

Language

study

languages

gender

data

challenging

study

variation

focus

paper

approaches

transfer

study

variation

variables

Techniques

computational linguistics

hand

standard

statistical

data

reduction

techniques

problem

question

abstract

levels

variation

paper

variation


Input: A Method For Abstracting Newspaper Articles By Using Surface Clues This paper describes a system which automatically creates an abstract of a newspaper article by selecting important sentences of a given text. To determine the importance of a sentence, several superficial features are considered, and weights for features are determined by multiple-regression analysis of a hand processed corpus.

Method

Newspaper

Surface

paper

system

abstract

newspaper

sentences

text

importance

sentence

features

weights

features

multiple-regression

analysis

hand

processed

corpus

paper

system

analysis

corpus

abstract

newspaper

sentences

text


Input: XML And Multilingual Document Authoring: Convergent Trends Typical approaches to XML authoring view a XML document as a mixture of structure (the tags) and surface (text between the tags). We advocate a radical approach where the surface disappears from the XML document altogether to be handled exclusively by rendering mechanisms. This move is based on the view that the author' s choices when authoring XML documents are best seen as language-neutral semantic decisions, that the structure can then be viewed as interlingual content, and that the textual output should be derived from this content by language-specific realization mechanisms, thus assimilating XML authoring to Multilingual Document Authoring. However, standard XML tools have important limitations when used for such a purpose: (1) they are weak at propagating semantic dependencies between different parts of the structure, and, (2) current XML rendering tools are ill-suited for handling the grammatical combination of textual units. We present two related proposals for overcoming these limitations: one (GF) originating in the tradition of mathematical proof editors and constructive type theory, the other (IG), a specialization of Definite Clause Grammars strongly inspired by GF.

Document

approaches

document

mixture

structure

tags

surface

text

tags

approach

surface

document

mechanisms

based

choices

documents

language-neutral

semantic

decisions

structure

content

output

content

language-specific

realization

mechanisms

Document

standard

tools

limitations

purpose

semantic

dependencies

parts

structure

current

tools

combination

units

proposals

limitations

type

theory

Clause

mechanisms

surface

output

content

limitations

tools


Input: Automatic Semantic Grouping In A Spoken Language User Interface Toolkit With the rapid growth of real application domains for NLP systems, there is a genuine demand for a general toolkit from which programmers with no linguistic knowledge can build specific NLP systems. Such a toolkit should provide an interface to accept sample sentences and convert them into semantic representations so as to allow programmers to map them to domain actions. In order to reduce the workload of managing a large number of semantic forms individually, the toolkit will perform what we call semantic grouping to organize the forms into meaningful groups. In this paper, we present three semantic grouping methods: similarity-based, verb-based and category-based grouping, and their implementation in the SLUI toolkit. We also discuss the pros and cons of each method and how they can be utilized according to the different domain needs.

Automatic

Semantic

Spoken Language

User Interface

application

domains

NLP systems

linguistic knowledge

NLP systems

provide

interface

sample

sentences

semantic representations

representations

map

domain

actions

order

number

semantic

forms

perform

call

semantic

forms

paper

semantic

methods

similarity-based

verb-based

category-based

implementation

cons

method

domain

semantic representations

sentences

paper

methods


Input: Paradigmatic Morphology We present a notation for the declarative statement of morphological relationships and lexical rules, based on the traditional notion of Word and Paradigm Elsewhere Condition, string equations

Morphology

notation

relationships

lexical

rules

based

notion

Word

Paradigm

string

equations

notation

relationships


Input: Selective Magic HPSG Parsing We propose a parser for constraint-logic grammars implementing HPSG that combines the advantages of dynamic bottom-up and advanced top-down control. The parser allows the user to apply magic compilation to specific constraints in a grammar which as a result can be processed dynamically in a bottom-up and goal-directed fashion. State of the art top-down processing techniques are used to deal with the remaining constraints. We discuss various aspects concerning the implementation of the parser as part of a grammar development system.

Parsing

propose

parser

constraint-logic

implementing

advantages

advanced

control

parser

user

apply

compilation

constraints

result

processed

goal-directed

fashion

processing

techniques

deal

constraints

aspects

concerning

implementation

parser

part

development

system

control

parser

compilation

constraints

processing

constraints

parser

system


Input: Representing Text Chunks " Dividing sentences in chunks of words is a useful preprocessing step for parsing, information extraction and information retrieval. (Ramshaw and Marcus, 1995) have introduced a " " convenient " " data representation for chunking by converting it to a tagging task. In this paper we will examine seven different data representations for the problem of recognizing noun phrase chunks. We will show that the the data representation choice has a minor influence on chunking performance. However, equipped with the most suitable data representation, our memory-based learning chunker was able to improve the best published chunking results for a standard data set. "

Text

sentences

chunks

words

step

parsing

information extraction

information retrieval

data

representation

chunking

tagging

task

paper

data

representations

problem

noun phrase

chunks

data

representation

choice

influence

chunking

performance

data

representation

memory-based

learning

improve

chunking

results

standard

data

words

sentences

data

representation

paper

representations

choice

performance


Input: Detection Of Japanese Homophone Errors By A Decision List Including A Written Word As A Default Evidence In this paper, we propose a practical method to detect Japanese homophone errors in Japanese texts. It is very important to detect homophone errors in Japanese revision systems because Japanese texts suffer from homophone errors frequently. In order to detect homophone errors, we have only to solve the homophone problem. We can use the decision list to do it because the homophone problem is equivalent to the word sense disambiguation problem. However, the homophone problem is different from the word sense disambiguation problem because the former can use the written word but the latter cannot. In this paper, we incorporate the written word into the original decision list by obtaining the identifying strength of the written word. The improved decision list can raise the F-measure of error detection.

Detection

Japanese

Decision

List

Word

Default

Evidence

paper

propose

method

Japanese

errors

Japanese

texts

errors

Japanese

revision

systems

Japanese

texts

errors

order

errors

solve

problem

decision

list

problem

word sense disambiguation

problem

problem

word sense disambiguation

problem

word

paper

word

decision

list

strength

word

improved

decision

list

error

detection

Word

List

errors

revision

word

list

method

errors

errors

texts

strength

word


Input: New Models For Improving Supertag Disambiguation In previous work, supertag disambiguation has been presented as a robust partial parsing technique. In this paper we present two approaches: contextual models, which exploit a variety of features in order to improve supertag performance, and class-based models, which assign sets of supertags to words in order to substantially improve accuracy with only a slight increase in ambiguity.

Models

Disambiguation

disambiguation

robust

partial

parsing

technique

paper

approaches

models

variety

features

order

improve

performance

class-based models

words

order

improve

accuracy

increase

ambiguity

Models

Disambiguation

class-based models

words

models

paper

features

performance


Input: Japanese Dependency Structure Analysis Based On Maximum Entropy Models This paper describes a dependency structure analysis of Japanese sentences based on the maximum entropy models. Our model is created by learning the weights of some features from a training corpus to predict the dependency between bunsetsus or phrasal units. The dependency accuracy of our system is 87. 2% using the Kyoto University corpus. We discuss the contribution of each feature set and the relationship between the number of training data and the accuracy.

Japanese

Dependency Structure

Analysis

Based

Maximum Entropy

Models

paper

dependency structure

analysis

Japanese

sentences

based

maximum entropy models

model

weights

features

training corpus

dependency

units

dependency

accuracy

system

University

corpus

contribution

feature set

relationship

number

training

data

accuracy

Models

Analysis

weights

model

paper

analysis

accuracy

system


Input: Reranking And Self-Training For Parser Adaptation " Statistical " parsers trained and tested on the Penn Wall Street Journal (wsj) treebank have shown vast improvements over the last 10 years. Much of this improvement, however, is based upon an ever-increasing number of features to be trained on (typically) the wsj treebank data. This has led to concern that such parsers may be too finely tuned to this corpus at the expense of portability to other genres. Such worries have merit. The standard " " Charniak parser " " checks in at a labeled precision-recall f-measure of 89. 7% on the Penn WSJ test set, but only 82. 9% on the test set from the Brown treebank corpus. This paper should allay these fears. In particular, we show that the reranking parser described in Charniak and Johnson (2005) improves performance of the parser on Brown to 85. 2%. Furthermore, use of the self-training techniques described in (McClosky et al., 2006) raise this to 87. 8% (an error reduction of 28%) again without any use of labeled Brown data. This is remarkable since training the parser and reranker on labeled Brown data achieves only 88. 4%. "

Training

Parser

Adaptation

Statistical

parsers

trained

tested

Wall Street Journal

improvements

improvement

based

number

features

trained

data

concern

parsers

corpus

portability

genres

standard

parser

checks

precision-recall

test set

test set

corpus

paper

parser

improves

performance

parser

self-training

techniques

error

reduction

data

training

parser

data

Wall Street Journal

parsers

features

improvement

corpus

parsers


Input: Automatic Classification Of Verbs In Biomedical Texts Lexical classes, when tailored to the application and domain in question, can provide an effective means to deal with a number of natural language processing (nlp) tasks. While manual construction of such classes is difficult, recent research shows that it is possible to automatically induce verb classes from cross-domain corpora with promising accuracy. We report a novel experiment where similar technology is applied to the important, challenging domain of biomedicine. We show that the resulting classification, acquired from a corpus of biomedical journal articles, is highly accurate and strongly domain-specific. It can be used to aid bio-nlp directly or as useful material for investigating the syntax and semantics of verbs in biomedical texts.

Automatic

Classification

Texts

Lexical

classes

application

domain

question

provide

deal

number

natural language processing

tasks

manual

construction

classes

research

verb classes

classes

cross-domain

corpora

accuracy

report

experiment

technology

applied

challenging

domain

resulting

classification

corpus

journal

domain-specific

syntax

semantics

verbs

texts

Classification

Texts

construction

classes

technology

domain

corpus

classification

verb classes

corpora

verbs

texts


Input: Word Alignment In English-Hindi Parallel Corpus Using Recency-Vector Approach: Some Studies Word alignment using recency-vector based approach has recently become popular. One major advantage of these techniques is that unlike other approaches they perform well even if the size of the parallel corpora is small. This makes these algorithms worth-studying for languages where resources are scarce. In this work we studied the performance of two very popular recency-vector based approaches, proposed in (Fung and McKeown, 1994) and (Somers, 1998), respectively, for word alignment in English-Hindi parallel corpus. But performance of the above algorithms was not found to be satisfactory. However, subsequent addition of some new constraints improved the performance of the recency-vector based alignment technique significantly for the said corpus. The present paper discusses the new version of the algorithm and its performance in detail.

Word Alignment

English-

Parallel Corpus

Vector

Approach

Studies

Word alignment

recency-vector

based

approach

advantage

techniques

approaches

perform

size

parallel corpora

algorithms

languages

resources

studied

performance

recency-vector

based

approaches

proposed

word alignment

alignment

English

parallel corpus

performance

algorithms

addition

constraints

improved

performance

recency-vector

based

alignment

technique

corpus

paper

version

algorithm

performance

detail

word alignment

English

paper

algorithm


Input: Semi-Supervised Training For Statistical Word Alignment We introduce a semi-supervised approach to training for statistical machine translation that alternates the traditional Expectation Maximization step that is applied on a large training corpus with a discriminative step aimed at increasing word-alignment quality on a small, manually word-aligned sub-corpus. We show that our algorithm leads not only to improved alignments but also to machine translation outputs of higher quality.

Training

Statistical

Word Alignment

approach

training

statistical machine translation

machine translation

Expectation

Maximization

step

applied

training corpus

corpus

step

increasing

word-alignment

quality

word-aligned

sub-corpus

algorithm

improved

alignments

machine translation

outputs

quality

approach

statistical machine translation

step

training corpus

step

quality


Input: You Can' t Beat Frequency (Unless You Use Linguistic Knowledge)-A Qualitative Evaluation Of Association Measures For Collocation And Term Extraction In the past years, a number of lexical association measures have been studied to help extract new scientific terminology or general-language collocations. The implicit assumption of this research was that newly designed term measures involving more sophisticated statistical criteria would outperform simple counts of cooccurrence frequencies. We here explicitly test this assumption. By way of four qualitative criteria, we show that purely statistics-based measures reveal virtually no difference compared with frequency of occurrence counts, while linguistically more informed metrics do reveal such a marked difference.

Frequency

Linguistic Knowledge

Evaluation

Association

Collocation

Term

Extraction

number

lexical

association

studied

help

extract

terminology

general-language

collocations

assumption

research

designed

term

statistical

criteria

simple

frequencies

test

assumption

criteria

statistics-based

difference

frequency

occurrence

metrics

difference

Evaluation

Extraction


Input: A Rote Extractor With Edit Distance-Based Generalisation And Multi-Corpora Precision Calculation In this paper, we describe a rote extractor that learns patterns for finding semantic relationships in unrestricted text, with new procedures for pattern generalization and scoring. These include the use of part-of-speech tags to guide the generalization, Named Entity categories inside the patterns, an edit-distance-based pattern generalization algorithm, and a pattern accuracy calculation procedure based on evaluating the patterns on several test corpora. In an evaluation with 14 entities, the system attains a precision higher than 50% for half of the relationships considered.

Extractor

Distance-

Based

Corpora

Precision

Calculation

paper

extractor

patterns

semantic

relationships

text

procedures

pattern

generalization

include

part-of-speech

tags

generalization

Named

Entity

categories

patterns

edit-distance-based

pattern

generalization

algorithm

pattern

accuracy

calculation

procedure

based

evaluating

patterns

test

corpora

evaluation

entities

system

precision

relationships

paper

extractor

procedures

generalization


Input: An Empirical Study Of Chinese Chunking In this paper, we describe an empirical study of Chinese chunking on a corpus, which is extracted from UPENN Chinese Treebank-4 (CTB4). First, we compare the performance of the state-of-the-art machine learning models. Then we propose two approaches in order to improve the performance of Chinese chunking. 1) We propose an approach to resolve the special problems of Chinese chunking. This approach extends the chunk tags for every problem by a tag-extension function. 2) We propose two novel voting methods based on the characteristics of chunking task. Compared with traditional voting methods, the proposed voting methods consider long distance information. The experimental results show that the SVMs model outperforms the other models and that our proposed approaches can improve performance significantly.

Study

Chinese

paper

study

Chinese

chunking

corpus

extracted

Chinese

performance

machine

models

propose

approaches

order

improve

performance

Chinese

chunking

propose

approach

problems

Chinese

chunking

approach

chunk

tags

problem

tag-extension

function

propose

methods

based

characteristics

chunking

task

methods

proposed

methods

distance

information

experimental

results

model

models

proposed

approaches

improve

performance

Study

Chinese

chunking

corpus

chunking

methods

methods

methods

model

models

approaches

performance


Input: Soft Syntactic Constraints For Word Alignment Through Discriminative Training Word alignment methods can gain valuable guidance by ensuring that their alignments maintain cohesion with respect to the phrases specified by a monolingual dependency tree. However, this hard constraint can also rule out correct alignments, and its utility decreases as alignment models become more complex. We use a publicly available structured output SVM to create a max-margin syntactic aligner with a soft cohesion constraint. The resulting aligner is the first, to our knowledge, to use a discriminative learning method to train an ITG bitext parser.

Syntactic

Word Alignment

Alignment

Training

Word alignment

methods

gain

alignments

cohesion

respect

phrases

dependency tree

constraint

rule

alignments

utility

alignment models

models

complex

structured

output

syntactic

cohesion

constraint

resulting

knowledge

learning method

method

train

parser

Syntactic

Word Alignment

learning method

parser

constraint

alignments

complex

alignment models


Input: A Bio-Inspired Approach For Multi-Word Expression Extraction This paper proposes a new approach for Multi-word Expression (MWE) extraction on the motivation of gene sequence alignment because textual sequence is similar to gene sequence in pattern analysis. Theory of Longest Common Subsequence (LCS) originates from computer science and has been established as affine gap model in Bioinformatics. We perform this developed LCS technique combined with linguistic criteria in MWE extraction. In comparison with traditional n-gram method, which is the major technique for MWE extraction, LCS approach is applied with great efficiency and performance guarantee. Experimental results show that LCS-based approach achieves better results than n-gram.

Approach

Word

Expression

Extraction

paper

proposes

approach

Multi-word

Expression

extraction

motivation

gene

sequence

alignment

sequence

gene

sequence

pattern

analysis

Theory

Common

Subsequence

computer science

gap

model

perform

technique

criteria

extraction

comparison

n-gram

method

technique

extraction

approach

applied

efficiency

performance

Experimental

results

LCS-based approach

approach

results

n-gram

Approach

Extraction

extraction

Expression

technique

extraction

paper

approach

LCS-based approach

results


Input: Graph Branch Algorithm: An Optimum Tree Search Method For Scored Dependency Graph With Arc Co-Occurrence Constraints " Various kinds of scored dependency graphs are proposed as packed shared data structures in combination with optimum dependency tree search algorithms. This paper classifies the scored dependency graphs and discusses the specific features of the " " Dependency Forest " " (DF) which is the packed shared data structure adopted in the " " Preference Dependency Grammar " " (PDG), and proposes the " " Graph Branch Algorithm " " for computing the optimum dependency tree from a DF. This paper also reports the experiment showing the computational amount and behavior of the graph branch algorithm. "

Algorithm

Tree

Search

Method

Dependency Graph

Arc

Occurrence

kinds

dependency graphs

proposed

data

structures

combination

dependency tree

search algorithms

paper

dependency graphs

features

Dependency

Forest

data

structure

Preference

Dependency Grammar

proposes

Algorithm

computing

dependency tree

paper

reports

experiment

computational

amount

behavior

algorithm

Algorithm

computing

behavior

algorithm


Input: Translating HPSG-Style Outputs Of A Robust Parser Into Typed Dynamic Logic The present paper proposes a method by which to translate outputs of a robust HPSG parser into semantic representations of Typed Dynamic Logic (TDL), a dynamic plural semantics defined in typed lambda calculus. With its higher-order representations of contexts, TDL analyzes and describes the inherently inter-sentential nature of quantification and anaphora in a strictly lexicalized and compositional manner. The present study shows that the proposed translation method successfully combines robustness and descriptive adequacy of contemporary semantics. The present implementation achieves high coverage, approximately 90%, for the real text of the Penn Treebank corpus.

Robust

Parser

Logic

paper

proposes

method

translate

outputs

robust

parser

semantic representations

representations

Logic

semantics

typed

calculus

higher-order

representations

contexts

nature

quantification

manner

study

proposed

translation

method

robustness

adequacy

semantics

implementation

coverage

text

Penn Treebank

corpus

paper

method

semantic representations

outputs

representations

contexts

robustness

method

implementation

coverage

text

corpus


Input: Adding Syntax To Dynamic Programming For Aligning Comparable Texts For The Generation Of Paraphrases Multiple sequence alignment techniques have recently gained popularity in the Natural Language community, especially for tasks such as machine translation, text generation, and paraphrase identification. Prior work falls into two categories, depending on the type of input used: (a) parallel corpora (e. g., multiple translations of the same text) or (b) comparable texts (non-parallel but on the same topic). So far, only techniques based on parallel texts have successfully used syntactic information to guide alignments. In this paper, we describe an algorithm for incorporating syntactic features in the alignment process for non-parallel texts with the goal of generating novel paraphrases of existing texts. Our method uses dynamic programming with alignment decision based on the local syntactic similarity between two sentences. Our results show that syntactic alignment outrivals syntax-free methods by 20% in both grammatically and fidelity when computed over the novel sentences generated by alignment-induced finite state automata.

Syntax

Dynamic Programming

Texts

Generation

sequence

alignment

techniques

gained

popularity

Natural Language

community

tasks

machine translation

translation

text generation

identification

categories

type

input

parallel corpora

translations

text

texts

topic

techniques

based

parallel texts

texts

syntactic information

information

alignments

paper

algorithm

syntactic features

alignment

process

non-parallel texts

goal

generating

texts

method

dynamic programming

programming

alignment

decision

based

syntactic

similarity

sentences

results

syntactic

alignment

syntax-free

methods

sentences

generated

alignment-induced

Texts

Generation

translations

text

parallel texts

techniques

syntactic information

alignments

dynamic programming

method

similarity

decision

paper

algorithm

alignment

methods


Input: Clavius: Bi-Directional Parsing For Generic Multimodal Interaction We introduce a new multi-threaded parsing algorithm on unification grammars designed specifically for multimodal interaction and noisy environments. By lifting some traditional constraints, namely those related to the ordering of constituents, we overcome several difficulties of other systems in this domain. We also present several criteria used in this model to constrain the search process using dynamically loadable scoring functions. Some early analyses of our implementation are discussed.

Parsing

Interaction

parsing

algorithm

unification

designed

interaction

environments

constraints

ordering

constituents

difficulties

systems

domain

criteria

model

search

process

functions

analyses

implementation

Parsing

Interaction

parsing

interaction

constraints

constituents

difficulties

systems

criteria

process


Input: Is It Correct?-Towards Web-Based Evaluation Of Automatic Natural Language Phrase Generation This paper describes a novel approach for the automatic generation and evaluation of a trivial dialogue phrases

Based

Evaluation

Automatic

Natural Language

Phrase

Generation

paper

approach

automatic

generation

evaluation

dialogue

phrases

Evaluation

Generation

paper

approach

generation

phrases


Input: A Machine Translation System From Japanese Into English-Another Perspective Of MT Systems A machine translation system from Japanese into English is described. The system aims at translation of computer manuals, and basically follows to the transfer approach. The design principles of the system are discussed in detail, together with the overall constructions of the system. Especially, the effectiveness of lexicon-based procedures, i. e. lexicon-based analysis, transfer, and synthesis, is emphasized. Most of the linguistic phenomena are treated by using lexical descriptions and lexical rules, instead of by general syntactic rules. Because Japanese and English belong to quite different language families, much more structural transfers are necessary than in other MT systems among European languages. Special cares have been paid for designing the transfer component. Some translation results are also given to illustrate the current abilities of the system.

Machine Translation System

Translation System

Japanese

English

Perspective

Systems

machine translation system

translation system

Japanese

English

system

translation

computer

manuals

transfer

approach

design

principles

system

detail

constructions

system

effectiveness

lexicon-based

procedures

lexicon-based

analysis

transfer

synthesis

phenomena

lexical

descriptions

lexical

rules

syntactic

rules

Japanese

English

language

structural

transfers

MT systems

languages

designing

transfer

component

translation results

current

abilities

system

Machine Translation System

Japanese

machine translation system

Japanese

translation

manuals

principles

system

abilities

system

effectiveness

procedures


Input: Referential Nets With Attributes One of the essential problems in natural language production and understanding is the problem of processing referential relations. In this paper I describe a model for representing and processing referential relations: referential nets with attributes. Both processes (analyzing and generating referential expressions) are controlled by attributes. There are two types of attributes, on one hand, the ones to the internal substitutes of the objects spoken about, on the other hand, the ones to the descriptions of these objects.

problems

natural language

understanding

problem

processing

relations

paper

model

processing

relations

processes

generating

expressions

types

hand

objects

hand

descriptions

objects

paper

model

processing

relations


Input: A Multilayered Approach To The Handling Of Word Formation The treatment of word formations has until recently been a neglected topic in natural language AI research. This paper proposes a multilayered approach to word formation which treats derivatives and compounds on several different levels of processing within a natural language dialogue system. Analysis and generation strategies being developed for the dialogue system HAM-ANS are described. Identification of word format ions, semantic interpretation, and evaluation in the context of a dialogue are the main levels of analysis on which the system successively attempts to infer the implicit relations between word formation components. Generation of word formations is viewed as a process comparable to the generation of elliptical utterances.

Approach

Word

Formation

treatment

word

formations

topic

natural language

research

paper

proposes

approach

word

formation

levels

processing

natural language

language

dialogue system

system

Analysis

generation

strategies

developed

dialogue system

system

Identification

word

format

ions

semantic interpretation

evaluation

context

dialogue

main

levels

analysis

system

relations

word

formation

components

Generation

word

formations

process

generation

utterances

paper

approach

natural language

dialogue system

strategies

dialogue system

word

utterances


Input: The Anatomy Of A Systemic Choice Choice is one of the most prominent organizing concepts in systemic linguistics. Languages are described in terms of the choices available to the speaker and the relationships of those choices to each other and to the language produced. This paper addresses the problems of

Choice

Choice

concepts

linguistics

Languages

terms

choices

relationships

choices

language

paper

problems

paper

problems


Input: Parsing German The first part of this paper is dedicated to an overview of the parser of the system VIE-LANG (Viennese Language Understanding System). The parser is a production system which uses an interleaved method that combines syntax and semantics. It parses directly into the internal representation of the system, without producing an. intermediate syntactic structure. The last part discusses the relationship between some special features of the German language, and properties of the parser that originate in the language.

Parsing

part

paper

overview

parser

system

Language Understanding System

parser

production system

system

method

syntax

semantics

parses

representation

system

syntactic structure

part

relationship

features

language

properties

parser

language

paper

parser

syntax

method

language

parser

representation

system

features

language


Input: Definite Noun Phrases And The Semantics Of Discourse Discourse Representation Theory (DRT), developed by Hans Kamp several years ago (Kamp 1981), belongs, together with Irene Heims narrowly related File Change Semantics (Heim 1982) and Situation Semantics (Barwise/Perry 1983), to a group of theoretical approaches which in the early Eighties introduced a dynamic, context-oriented perspective into the semantics of natural language. This recent development in theoretical semantics indicates a shift of interest towards topics that have been familiar in natural language processing research for the last decade: among others, the interpretation of new utterances with respect to a given context, and integration of the utterance information into that context; the step-by-step construction of representations for larger pieces of discourse; the investigation of text coherence phenomena; and the description of referential processes. The core of DRT (and File Change Semantics) is the treatment of indefinite noun phrases as reference establishing terms (as opposed to their standard truth-conditional quantifier analysis, but in accordance with the treatmant of indefinites in NLP research) and definite noun phrases (pronouns as well as full NPs) as anaphoric expressions. It is one of the theoretically most appealing features of these theories that they provide simple unified accounts for all indefinites, and for all definites, respectively. This theoretical simplicity stands however in sharp contrast to the complexity of the process of etablishing reference observed in NLP research, and the variety of phenomena and linguistic levels involved. On the one hand, this contrast is quite natural: As a semantically motivated theory, DRT should not be expected to incorporate every detail of inferencing necessary to come up with an interpretation for a specific utterance in a given context; it can better be thought of as an interface relating theoretical, truth-conditional semantics and the genuinely pragmatic work of text understanding. On the other hand, if DRT is seriously intended to bridge the gap between theoretical linguistics and the NLP approach, it should take into consideration as many factual restrictions on NP reference, and distinctions among subtypes of referential expressions, as is possible in a systematic and descriptive way. Several extensions of the standard system are at work, e. g. for the treatment of plural and temporal anaphora. Little, however, has yet been done to arrive at a closer view of the analysis of (singular) definite noun phrases, once the basic concepts had been established. The only attempt I know about is by Kamp himself, described in Kamp (1983), an unpublished fragment. In this talk I will first give a short overview of the basic DRT system, and sketch Kamp' s proposal for the treatment of definite noun phrases. Then I will indicate how the basic reference establishing function and the' side-effects' of different types of definite NPs can be described in more detail. In doing this, I will refer to the work about anaphora done in the NLP area (esp. by Barbara Grosz, Candy Sidner, and Bonnie Webber), integrating some of their assumptions into the DRT framework, and critically commenting on some others.

Noun

Semantics

Discourse

Discourse Representation Theory

developed

Semantics

Situation

Semantics

approaches

context-oriented

perspective

semantics

natural language

language

development

semantics

shift

topics

natural language processing

research

interpretation

utterances

respect

context

integration

utterance

information

context

step-by-step

construction

representations

discourse

investigation

text

coherence

phenomena

description

processes

core

Semantics

treatment

noun phrases

phrases

reference

terms

standard

quantifier

analysis

research

noun phrases

expressions

features

theories

provide

simple

simplicity

contrast

complexity

process

reference

research

variety

phenomena

levels

hand

contrast

natural

theory

detail

inferencing

interpretation

utterance

context

interface

semantics

text

understanding

hand

gap

linguistics

approach

consideration

restrictions

reference

distinctions

expressions

extensions

standard

system

treatment

analysis

noun phrases

basic

concepts

fragment

overview

basic

system

proposal

treatment

noun phrases

phrases

basic

reference

function

side-effects

types

detail

area

assumptions

framework

Semantics

Discourse

semantics

natural language

investigation

phenomena

treatment

noun phrases

treatment

noun phrases

context

interpretation

context

interpretation

information

utterance

extensions

system

description

processes


Input: Towards The Automatic Acquisition Of Lexical Data " Creating a knowledge base has always been a bottleneck in the implementation of AI systems. This is also true for Natural Language Understanding (NEU) systems, particularly for data-driven ones. While a perfect system for automatic acquisition of all sorts of knowledge is still feir from being realized, partial solutions are possible. This holds especially for lexical data. Nevertheless, the task is not trivial, in particular when dealing with languages rich in inflectional Horms like German. Our: system is to be used by persons with no specific linguistic knowledge, thus linguistic expertise has been put into the system to ascertain correct classification of words. Classification is done by means of a small rule based system with Lexical knowledge and language-specific heuristics. The key idea is the identification of three sorts of knowledge which are processed distinctly and the optimal use of knowledge already contained in the existing Lexicon. 1 Introduction in this paper we introduce a system for the semi-automatic enlargement of a morphological 1 ex icon. If forms part of VIE-BANG, a German Language dialogue system (Buchberger et al. 1982). VI K-l. ANG serves not only as an ob ject but as a meta system as we 11: i ts knowledge base is to be enlarged, and its facilities are used L: o support that process: the parsor serves to analyze the i nput to the acquisj ti on system, the generator i. s used to provide exampl es. Ln contrast to English the morphological analysis of German words is no trivial task, due to two causes:-First, there is a rich inflectional system, consisting of about 60 different endings (where most endings have various different interpretations), some prefixes (' go-PPP, "

Automatic

Acquisition

Lexical

Data

knowledge base

base

implementation

systems

Natural Language Understanding

systems

data-driven

system

automatic

acquisition

knowledge

partial

solutions

lexical

data

task

dealing

languages

system

linguistic knowledge

system

classification

words

Classification

rule

based

system

Lexical knowledge

language-specific

identification

knowledge

processed

optimal

knowledge

Lexicon

Introduction

paper

system

semi-automatic

icon

forms

part

Language

dialogue system

system

knowledge base

support

process

system

generator

provide

contrast

English

morphological analysis

analysis

words

task

due

system

interpretations

prefixes

Acquisition

Data

classification

words

Lexical knowledge

Classification

knowledge base

systems

paper

system

morphological analysis

words


Input: The PSI/PHI Architecture For Prosodic Parsing In is in as a a

Architecture

Parsing

Architecture

Parsing


Input: Optimization Algorithms Of Deciphering As The Elements Of A Linguistic Theory This paper presents an outline of the linguistic theory which may be identified with the partially ordered set of optimization algorithms of deciphering. An algorithm of deciphering is the operational definition of a given linguistic phenomenon which han the following three components: a set of admissible solutions, an objective function and a procedure which finds out the ministurn or the maximum of the objective function. The paper contains the description of the four algorithms of the proposed type: 1. The algorithm which classifies the letters into vowels and consonants. 2. The algorithm which identifies the morphemes in the text without the boundaries between words. 3. The algorithm whioh finds out the dependency tree of a sentence.

Optimization

Algorithms

Linguistic Theory

paper

outline

linguistic theory

ordered

optimization

algorithms

algorithm

definition

phenomenon

components

solutions

objective function

procedure

objective function

paper

description

algorithms

proposed

type

algorithm

vowels

consonants

algorithm

text

boundaries

words

algorithm

dependency tree

tree

sentence

description

algorithms

boundaries

words

dependency tree

sentence


Input: Tenets For An Interlingual Representation Of Definite NPs The main goal of this paper (as in Keenan and Stavi 1986) is to characterize the possible determiner denotations in order to develop a computational approach that makes explicit use of this information. To cope with the constraints that languages impose when generating determiners, a computational model has to follow the laws that map d finiteness to structures and strings and viceversa. In the following proposal I distantiate from K. B hlers Deixis Theory and Weinrichs (76) proposal where indefinites suggest subsequent information, while definite point out facts from the previous information. This very general position is insufficient if we want to formalize NP-definiteness. The semantics of NP defmiteness must be captured adequately in computational frameworks for such tasks as answering quantified NL--questions, or in a MT system to convert NPs from one language into another. In the first part of this paper I draw a typology of defmiteness; later I reflect on the defmiteness of NPs in an IL-representation. The major result is given by the determiner generators. Defmiteness should be evaluated in a Q-A system and in MT. The extensive functionality of defmiteness is first elaborated in the parsing and results in an IL-representation; finally the determiner generators create correct morphological determiners and right determiner structures.

Representation

main

goal

paper

determiner

order

develop

computational

approach

information

constraints

languages

generating

determiners

computational model

map

structures

strings

proposal

Theory

proposal

information

information

semantics

computational

frameworks

tasks

questions

MT system

language

part

paper

typology

IL-representation

result

determiner

generators

evaluated

system

functionality

parsing

results

IL-representation

determiner

generators

determiners

determiner

structures

paper

typology


Input: Lexical Gaps And Idioms In Machine Translation This paper describes the treatment of lexical gaps, collocation information and idioms in the English to Portuguese machine translation system PORTUGA. The perspective is strictly bilingual, in the sense that all problems referenced above are considered to belong to the transfer phase, and not, as in other systems, to analysis or generation. The solution presented invokes a parser for the target language (Portuguese) that analyses, producing the corresponding graph structure, the multiword expression selected as the result of lexical transfer. This process seems to bring considerable advantage in what readability and ease of bilingual dictionary development is concerned, and to furnish maximal flexibility together with minimal storage requirements. Finally, it also provides complete independence between dictionary and grammar formalisms.

Lexical

Machine Translation

paper

treatment

lexical

gaps

collocation

information

idioms

English

machine translation system

translation system

perspective

sense

problems

transfer

phase

systems

analysis

generation

solution

parser

target language

analyses

structure

multiword expression

expression

result

lexical

transfer

process

advantage

readability

dictionary

development

concerned

flexibility

storage

requirements

provides

independence

dictionary

formalisms

paper

machine translation system

parser

multiword expression


Input: Intelligent Handling Of Weather Forecasts Some typical cases of intelligent handling of weather forecasts such as translation, visualization, etc. are decomposed into two subprocesses analysis and synthesis. Specific techniques are presented for analysis and synthesis of weather forecast texts as well as for generation of weather maps. These techniques deal with the weather forecasts at different levels syntactic, discourse and semantic. They are based on a conceptual model underlying weather forecasts as well as on formal descriptions of the means of expression used in particular natural and cartographic sublanguages.

cases

translation

visualization

analysis

synthesis

techniques

analysis

synthesis

texts

generation

maps

techniques

deal

levels

syntactic

discourse

semantic

based

model

descriptions

expression

natural


Input: Genetic NPs And Habitual VPs We propose a simple, intuitively satisfying treatment of the semantics of bare plural NPs. This treatment avoids the use of nonstandard logics, and avoids the need for systematic ambiguity of verb semantics.

propose

simple

treatment

semantics

treatment

logics

ambiguity

verb

semantics

treatment

semantics

ambiguity

semantics


Input: Using Linguistic, World, And Contextual Knowledge In A Plan Recognition Model Of Dialogue This paper presents a plan-based model of dialogue that combines world, linguistic, and contextual knowledge in order to recognize complex communicative actions such as expressing doubt. Linguistic knowledge suggests certain discourse acts, a speaker' s beliefs, and the strength of those beliefs; contextual knowledge suggests the most coherent continuation of the dialogue; and world knowledge provides evidence that the applicability conditions hold for those discourse acts that capture the relationship of the current utterance to the discourse as a whole.

Knowledge

Recognition

Model

Dialogue

paper

plan-based model

model

dialogue

knowledge

order

complex

actions

Linguistic knowledge

discourse

strength

knowledge

dialogue

world knowledge

provides

evidence

applicability

discourse

relationship

current

utterance

discourse

Model

Dialogue

paper

plan-based model


Input: Temporal Structure Of Discourse In this paper discourse segments are defined and a method for discourse segmentation primarily based on abduction of temporal relations between segments is proposed. This method is precise and computationally feasible and is supported by previous work in the area of temporal anaphora resolution.

Structure

Discourse

paper

discourse

segments

method

discourse

based

temporal relations

segments

proposed

method

supported

area

anaphora resolution

resolution

Structure

Discourse

method

discourse

method

anaphora resolution


Input: Organizing Dialogue From An Incoherent Stream Of Goals their reasoning for structure their dialogues. Instead, computer-generated conversation must rely on some other mechanism for its organisation. In this paper, we discuss such mechanism. We describe provides a guide for conversation. The template is built from schemata representing discourse convention. As goals arrive from the problem solver they are added to the template. Because accepted discourse structures are used to connect a new goal to the existing template, goals are organised into sub-groups that follow conventional, coherent patterns of discourse. We present JUDIS, an interface to distributed problem solver that uses this approach to organise dialogues from incoherent of goals.

Dialogue

Stream

reasoning

structure

dialogues

computer-generated

conversation

mechanism

paper

mechanism

provides

conversation

template

schemata

discourse

convention

goals

problem

solver

template

discourse structures

goal

template

goals

patterns

discourse

interface

distributed

problem

solver

approach

dialogues

goals

patterns

discourse


Input: Preventing False Temporal Implicatures: Interactive Defaults For Text Generation Given the causal and temporal relations between events in a knowledge base, what are the ways they can be described in text? Elsewhere, we have argued that during interpretation, the reader-hearer//must infer certain temporal information from knowledge about the world, language use and pragmatics. It is generally agreed that processes of Gricean implicature help determine the interpretation of text in context. But without a notion of logical con se quo ii ce to underwrite them, the inferences-often defeasible in nature-will appear arbitrary, and unprincipled. Hence, we have explored the requirements on a formal model of temporal implicature, and outlined one possible nonmonotonic framework for discourse interpretation (Lascarides &; Asher [1991], Lascarides Oberlander [1992a]). Here, we argue that if the writer-speaker 22077.

Defaults

Text Generation

temporal relations

relations

events

knowledge base

text

interpretation

information

knowledge

language

processes

help

interpretation

text

context

notion

con

inferences

nature

requirements

model

outlined

framework

discourse

interpretation

temporal relations

events

context

interpretation


Input: Design Tool Combining Keyword Analyzer And Case-Based Parser For Developing Natural Language Database Interfaces We have designed and experimentally implemented a tool for developing a natural language systems that can accept extra-grammatical expressions, keyword sequences, and linguistic fragments, as well as ordinary natural language queries. The key to this tool' s efficiency is its effective use of a simple keyword analyzer in combination with a conventional case-based parser. The keyword analyzer performs a majority of those queries which are simple data retrievals. Since it uses only keywords in any query, this analyzer is robust with regard to extra-grammatical expressions. Since little labor is required of the application designer in using the keyword analyzer portion of the tool, and since the case-based parser processes only those queries which the keyword analyzer fails to interpret, total labor required of the designer is less than that for a tool which employs a conventional case-based parser alone.

Design

Tool

Combining

Keyword

Analyzer

Case-

Based

Parser

Developing

Natural Language

Database

designed

implemented

tool

developing

natural language systems

language systems

expressions

keyword

sequences

fragments

natural language

queries

tool

efficiency

simple

keyword

analyzer

combination

case-based

parser

keyword

analyzer

performs

majority

queries

simple

data

retrievals

keywords

query

analyzer

robust

expressions

labor

required

application

keyword

analyzer

portion

tool

case-based

parser

processes

queries

keyword

analyzer

labor

required

tool

case-based

parser

Tool

Database

tool

natural language systems

robust

analyzer


Input: A Robust Approach For Handling Oral Dialogues Present limits of speech recognition and understanding in the context of free spoken language (altlwugh with a limited vocabulary) have perverse effects on the flow of the dialogue with a system. Typically a non robust dialogue manager will fail to face with these limits and conversations will often be a failure. This paper presents some possibilities of a structural approach for handling communication failures in task-oriented oral dialogues. Several types of communication failures are presented and explained. They must be dealt with by the dialogue manager if we strike to have a robust system. The exposed strategies for handling these failures are based on a structural approach of the conversation and are implemented in the SUNDIAL system. We first recall some aspects of the model and then describe the strategies for preventing and repairing communication failure in oral conversations with a system.

Robust

Approach

limits

speech recognition

recognition

understanding

context

language

vocabulary

effects

dialogue

system

robust

dialogue

manager

limits

conversations

paper

possibilities

structural

approach

communication

task-oriented

dialogues

types

communication

dealt

dialogue

manager

robust

system

strategies

based

structural

approach

conversation

implemented

system

recall

aspects

model

strategies

repairing

communication

conversations

system

limits

speech recognition

task-oriented

dialogues

paper

possibilities

system

repairing


Input: Causal Ambiguity In Natural Language: Conceptual Representation Of' parce Que/because' And' puisque/since' This research deals with the representation of causal relations found in texts written in natural language, in order for KALIPSOS [1], an NL-understanding and question-answering system, to encode causal information in conceptual graphs so as to handle causal information and reasoning. Natural languages such as French or English have many ways to express a causal relation. It can be syntactic (parce que/because) {provoquer/to produce), (Je me suis cass e la jambe el je n' ai pas pu venir/1 broke my leg and I couldn' t come), parce que/because puisque/since parce que/because puisque/since

Ambiguity

Natural Language

Representation

research

deals

representation

relations

texts

natural language

order

NL-understanding

question-answering system

information

information

reasoning

Natural languages

languages

English

relation

syntactic

representation

relations


Input: B-SURE: A Believed Situation And Uncertain-Action Representation Environment Tliis paper presents a system that is capable of representing situations, states, and nondeterniinistic nonmonotonic-outcome actions occurring in multiple possible worlds. The system supports explicit representations of actions and situations used in intentional action theory and situation theory, l oth types and instances are supported. Situations and states before and after nonmonotonic actions can be represented simultaneously. Agents have free will as to whether to choose to perform an action or not. Situations mid actions can have expected values, allowing the system to support decision-making and decision-based plan inferencing. The system can perform global reasoning simultaneously across multiple possible worlds, without being forced to extend each world explicitly. The resulting system is useful for Biich natural language tasks as plan recognition, intentions modeling, and parallel task scheduling.

Situation

Action

Representation

Environment

paper

system

situations

nonmonotonic-outcome

actions

system

supports

representations

actions

situations

action

theory

situation

theory

types

instances

supported

actions

perform

action

actions

system

support

decision-making

decision-based

inferencing

system

perform

reasoning

resulting

system

natural language

tasks

recognition

modeling

task

paper

system

system

decision-making


Input: An Architecture For A Universal Lexicon A Case Study On Shared Syntactic Information In Japanese, Hindi, Bengali, Greek, And English Pustejovsky, James, The Generative Lexicon, Computation al Linguistics, 1991

Architecture

Lexicon

Case Study

Study

Syntactic Information

Information

Japanese

Bengali

Greek

English

Lexicon

Computation

Linguistics

Case Study

Syntactic Information


Input: Logic Compression Of Dictionaries For Multilingual Spelling Checkers " To provide practical spelling checkers on micro-computers, good compression algorithms are essential. Current techniques used to compress lexicons for indo-Europcan languages provide efficient spelling checker. Applying the same methods to languages which have a different morphological system (Arabic, Turkish,...) gives insufficient results. To get better results, we apply other " " logical " " compression mechanisms based on the structure of the language itself. Experiments with multilingual dictionaries show a significant reduction rate attributable to our logic compression alone and even better results when using our method in conjunction with existing methods. KEY WORDS: "

Logic

Compression

provide

micro-computers

compression

algorithms

Current

techniques

lexicons

languages

provide

Applying

methods

languages

system

results

results

apply

compression

mechanisms

based

structure

language

Experiments

dictionaries

reduction

rate

logic

compression

results

method

conjunction

methods

WORDS

structure

mechanisms

Experiments

results


Input: CLAWS4: The Tagging Of The British National Corpus The main purpose of this paper is to describe the CLAWS4 general-purpose grammatical tagger, used for the tagging of the 100-million-word British National Corpus, of which c. 70 million words have been tagged at the time of writing (April 1994). tagsets input formats. output formats:

Tagging

Corpus

main

purpose

paper

general-purpose

tagging

million-word

Corpus

words

tagged

time

input

formats

output

formats

Tagging

Corpus

tagging

million-word


Input: Thesaurus-Based Efficient Example Retrieval By Generating Retrieval Queries From Similarities In example-based NLP, the problem of computational cost of example retrieval is severe, since the retrieval time increases in proportion to the number of examples in the database. This paper proposes a novel example retrieval method for avoiding full retrieval of examples. The proposed method has the following three features, 1) it generates

Thesaurus-

Based

Example

Retrieval

Generating

Retrieval

example-based

problem

computational

cost

example

retrieval

retrieval

time

increases

number

examples

database

paper

proposes

example

retrieval

method

retrieval

examples

proposed

method

features

generates

cost

retrieval

paper

method


Input: Discovering The Sounds Of Discourse Structure Extended Abstract It is widely accepted that discourses are composed of segments and that the recognition of segment boundaries is essential to a determination of discourse meaning (Grosz and Sidner, 1986). Written language has orthographic cues such as section headings, paragraph boundaries, and punctuation which can assist in identifying discourse structure. In spoken language, into-national variation provides essential information about discourse structure. For instance, it may be used to mark structural features of discourse at the global level, such as segment boundaries. Intonation also provides more local information about relations among utterances within a segment, for example indicating whether phrases are parenthetical. It can also help distinguish between different interpretations of phrases that can function either as cue phrases that indicate discourse segment boundaries or sentcntially to convey domain information. Finally, variations in intonational prominence may be used to convey information about the discourse status of entities referred to by definite noun phrases and pronouns. An understanding of intonational variation and the ways in which it carries information about discourse characteristics of spoken language is important for computer-based interpretation and generation of speech. From the interpretation perspective, this understanding may provide new techniques for identifying discourse structure. From the generation perspective, it would lead to more natural synthetic speech, making it possible to produce computer speech that is easier for people to understand and less susceptible to misinterpretation. Three major challenges have faced researchers attempting to discover the relationship between intonational features and the structure of spoken discourse. First, the collection of corpora of spontaneous speech has required the development of * The research described in this presentation was supported by the National Science Foundation, Grant IRI 94-04756. The research has been done collaboratively with Julia Hirschberg and Christine Nakatani. David Ahn provided invaluable technical assistance. new experimental methodologies. Whereas it is straightforward to have the same text read by many speakers, it is much more difficult to obtain similar samples of spontaneous speech from multiple speakers. Second, techniques must be developed to obtain reliable segmentations and labelings of the corpora. Because discourse structure is rooted in semantics rather than syntax, this has proved more difficult than tagging corpora for sentence structure. Third, measures of agreement among segmentations must be designed. In this area too, the semantic nature of discourse structure leads to a more complex problem than comparing sentence parse structures. This talk will begin with a summary of pilot studies that demonstrated reliable correlations of discourse structure and intonational features (Grosz and Hirschberg, 1992; Hirschbcrg and Grosz, 1992; Hirschbcrg and Grosz, 1994). It will then focus on a new corpus of direction-giving monologues, the Boston Directions Corpus (Nakatani et al., 1995a; Hirschberg and Nakatani, 1996). I will describe the methodology we developed to elicit fluent spontaneous direction-giving monologues ranging over a spectrum of planning complexity. Next I will describe the development of annotation instructions used to train labelers to segment spoken discourses (Nakatani et ah, 1995b) and will discuss agreement among segmentations on the Boston Directions Corpus obtained using these instructions. Then I will describe results of our analyses of the correlation between discourse structure and intonational features. Finally, I will present a list of challenges for future research in this area.

Discourse Structure

Abstract

discourses

segments

recognition

segment

boundaries

determination

discourse

language

cues

section

paragraph

boundaries

punctuation

discourse structure

language

variation

provides

information

discourse structure

instance

structural

features

discourse

level

segment

boundaries

Intonation

provides

information

relations

utterances

segment

example

phrases

help

interpretations

phrases

function

cue

phrases

discourse

segment

boundaries

domain

information

variations

prominence

information

discourse

status

entities

noun phrases

understanding

variation

information

discourse

characteristics

language

computer-based

interpretation

generation

speech

interpretation

perspective

understanding

provide

techniques

discourse structure

structure

generation

perspective

natural

speech

computer

speech

challenges

researchers

relationship

features

structure

discourse

collection

corpora

spontaneous speech

speech

required

development

research

presentation

supported

Science

Grant

research

provided

experimental

methodologies

text

samples

spontaneous speech

speech

techniques

developed

corpora

discourse structure

semantics

syntax

tagging

corpora

sentence structure

agreement

designed

area

semantic

nature

discourse structure

complex

problem

sentence

parse

structures

summary

pilot

studies

correlations

discourse structure

features

focus

corpus

direction-giving

Corpus

methodology

developed

direction-giving

spectrum

complexity

development

instructions

train

segment

discourses

agreement

Corpus

instructions

results

analyses

correlation

discourse structure

features

list

challenges

research

area

segments

discourses

boundaries

language

spontaneous speech

corpora

spontaneous speech

samples

recognition

segment

generation

speech

techniques

discourse structure

tagging

corpora

segment

discourses

semantics

discourse structure


Input: Parsing Spoken Language Without Syntax Parsing spontaneous speech is a difficult task because of the ungrammatical nature of most spoken utterances. To overpass this problem, we propose in this paper to handle the spoken language without considering syntax. We describe thus a microsemantic parser which is uniquely based on an associative network of semantic priming. Experimental results on spontaneous speech show that this parser stands for a robust alternative to standard ones.

Parsing

Spoken Language

Language

Syntax

Parsing

spontaneous speech

speech

task

nature

utterances

problem

propose

paper

language

syntax

parser

based

network

semantic

Experimental

results

spontaneous speech

parser

robust

alternative

standard

Parsing

Spoken Language

Parsing

spontaneous speech

nature

utterances


Input: Processing Word Order Variation Within A Modified ID/LP Framework " From a " " well represented sample of world languages Steele (1978) shows that about "

Processing

Word

Order

Variation

Framework

sample

languages

languages

sample


Input: A Compositional Approach To The Translation Of Temporal Expressions In The ROSETTA System This paper discusses the translation of temporal expressions, in the framework of the machine translation system Rosetta. The translation method of Rosetta, the' isomorphic grammar method', is based on Montague' s Compositionality Principle. It is shown that a compositional approach leads to a transparent account of the complex aspects of time in natural language and can be used for the translation of temporal expressions.

Approach

Translation

System

paper

translation

expressions

framework

machine translation system

translation

method

method

based

Principle

approach

complex

aspects

time

natural language

translation

expressions

paper

translation

translation

expressions


Input: Pragmatics In Machine Translation TEXAN is a system of transferi-oriented text analysis. Its linguistic concept is based on a communicative approach within the framework of speech act theory. In this view texts are considered to be the result of linguistic actions. It is assumed that they control the selection of translation equivalents. The transition of this concept of linguistic actions (text acts) to the model of computer analysis is performed by a context-free il locution grammar processing categories of actions and a propositional structure of states of affairs. The grammar which is related to a text lexicon provides the connection of these categories and the linguistic surface units of a single language.

Machine Translation

system

text analysis

analysis

concept

based

approach

framework

speech act

theory

texts

result

actions

control

selection

translation

transition

concept

actions

text

model

computer

analysis

performed

context-free

processing

categories

actions

structure

text

lexicon

provides

categories

surface

units

language

system

text analysis


Input: From Structure To Process Computer-Assisted Teaching Of Various Strategies For Generating Pronoun Constructions In French This paper describes an implemented tutoring system (2), designed to help students to generate clitic-constructions in French. While showing various ways of converting a given meaning structure into its corresponding surface expression, the system helps not only to discover what

Structure

Process

Computer-

Strategies

Generating

paper

implemented

system

designed

help

generate

structure

surface

expression

system

helps

paper

system


Input: Divided And Valency-Oriented Parsing In Speech Undstanding A parsing scheme for spoken utterances is proposed that deviates from traditional' one go' left to right sentence parsing in that it d vides the parsing process first into two aeperate parallel processes. Verbal constituents and nominal phrases (including prepositonal phrases) are treated seperately and only brought together in an utterance parser. This allows especially the utterance parser to draw on valency information right from beginning when amalgamating the nominal constituents to the verbal core by means of binary sentence rules. The paper also discusses problems of representing the valency information in case-frames arising in a spoken language environment.

Valency-

Parsing

Speech

parsing

scheme

utterances

proposed

sentence

parsing

parsing

process

processes

Verbal

constituents

phrases

including

phrases

utterance

parser

utterance

parser

valency

information

constituents

verbal

core

sentence

rules

paper

problems

valency

information

case-frames

language

environment

parsing

utterances


Input: Computational Phonology: Merged, Not Mixed Research into text-to-speech systems has become a rather important topic in the areas of linguistics and phonetics. Particularly for English, several text-to-speech systems have been established (cf. for example Hertz (1982), Klatt (1976)). For Dutch, text-to-speech systems are being developed at the University of Nijmegen (cf. Wester (1984)) and at the Universities of Utrecht and Leyden and the Institute of Perception Research (IPO) Eindhoven as well. In this paper we will be concerned with the grapheme-to-phoneme conversion component as part of the Dutch text-to-speech system which is being developed in Utrecht, Leyden and Eindhoven. One of our primary interests is that the grapheme-to-phoneme system not only has to generate the input for speech synthesis, either in allophone or diphone form, but that it had to be used for other purposes as well. Thus, the system has to satisfy the following demands:-its output must form a proper and flexible input for diphone as well as allophone synthesis;-it must be possible to easily generate phonematized lists on the basis of orthographic input;-it must be possible to automatically obtain information regarding the relation between graphemes and phonemes in texts;-the system has to be user-friendly, so that it can be addressed by linguists without computer training (for example to test their phonological rules). In our view, there are two aspects to a grapheme-to-phoneme conversion system: a linguistic and a computational one. The linguist, in fact, provides the grammar necessary for the conversion and the engineer implements this grammar into a computer system. Thus, knowledge about spelling and linguistics are separated

Computational

Phonology

Research

text-to-speech

systems

topic

areas

linguistics

English

text-to-speech

systems

example

text-to-speech

systems

developed

University

Universities

Research

paper

concerned

grapheme-to-phoneme

conversion

component

part

text-to-speech

system

developed

grapheme-to-phoneme

system

generate

input

speech synthesis

synthesis

form

purposes

system

following

output

form

input

synthesis

generate

lists

basis

input

information

relation

phonemes

texts

system

user-friendly

linguists

computer

training

example

test

rules

aspects

grapheme-to-phoneme

conversion

system

computational

linguist

provides

conversion

implements

computer

system

knowledge

spelling

linguistics

Research

text-to-speech

grapheme-to-phoneme

text-to-speech

grapheme-to-phoneme

speech synthesis

user-friendly

system


Input: Expressing Quantifier Scope In French Generation In this paper we propose a new method to express quantification and especially quantifier scope in French generation. Our approach is based on two points: the identification of the sentence components between which quantifier scope can indeed be expressed and a mechanism to reinforce the expression of quantifier scope. This approach is being integrated in a written French generator, called Herm s, which will become the generator of a portable natural language interface.

Quantifier

Scope

Generation

paper

propose

method

quantification

quantifier

scope

generation

approach

based

identification

sentence

components

quantifier

scope

mechanism

expression

quantifier

scope

approach

generator

called

generator

natural language interface

language

interface

paper

method

generator

natural language interface