Input: Constituent Coordination In Lexical-Functional Grammar " Abstract: This paper outlines a theory of constituent coordination for Lexical-Functional Grammar. On this theory LFG' s flat, unstructured sets arc used as the functional representation of coordinate constructions. Function-application is extended to sets by treating a sot formally as the generalization of its functional elements. This causes properties attributed externally to a coordinate structure to be uniformly distributed across its elements, without requiring additional grammatical specifications. Introduction A proper treatment of coordination has long been an elusive goal of both theoretical and computational approaches to language. The original transformational formulation in terms of the Coordinate Reduction rule (e. g./Dougherty 1970/) was quickly shown to have many theoretical and empirical inadequacies, and only recently have linguistic theories (e g, GPSG/Gazdar et al. 1985/, Categorial grammar (e. g./Steedman 1985/) made substantial progress on characterizing the complex restrictions on coordinate constructions and also on their semantic interpretations. Coordination has also presented descriptive problems for computational approaches. Typically these have been solved by special devices that are added to the parsing algorithms to analyze coordinate constructions that cannot easily be characterized in explicit rules of grammar. The best known examples of this kind of approach are SYSCONJ/Woods 1973/, ESP/Sager 1981/, and MSG/Dahl and McCord 1983/. Coordination phenomena are usually divided into two classes, the so-called constituent coordinations where the coordinated elements look like otherwise well-motivated phrasal constituents II), and nonconstituent coordination where the coordinated elements look like fragments of phrasal constituents (2). (1) (a) A girl saw Mary and ran to Iiill. (Coordinated verb phrases) (b) A girl saw and hoard Mary. (Coordinated verbs) (2) Iiill went to Chicago on Wednesday and New York on Thursday. Of course, what is or is not a well-motivated constituent depends on the details of the particular grammatical theory. Constituents in transformationally-oriented theories, for example, are units that simplify the feeding relations of transformational rules, whereas " " constituents " " in categorial grammars merely reflect the order of binary combinations and have no other special motivation. In lexical-functional grammar, surface constituents are taken to be the units of phonological interpretation. These may differ markedly from the units of functional or semantic interpretation, as shown in the analysis of Dutch cross serial dependencies given by/Bresnan et al. 1982/. N' onconstituent coordination, of course, presents a wide variety of complex and difficult descriptive problems, but constituent coordination also raises important linguistic issues. It is the latter that we focus on in this brief paper. To a first approximation, constituent coordinations can be analyzed as the result of taking two independent clauses and factoring out their common subparts. The verb coordination in (lb) is thus related to the fuller sentence coordination in (3). This intuition, which was the basis of the Coordinate Reduction Transformation, accounts for more complex patterns of acceptability such as (4) illustrates. The coordination in (4c) is acceptable because both (4a) and (4b) are, while (4e) is bad because of the independent subcategorization violation in (4d). (3) A girl saw Mary and a girl heard Mary. (4) (a) A gir l dedicated a pie to Bill. (b) A girl gave a pie to Bill. (c) A girl dedicated and gave a pie to Bill. (d) * A girl ate a pie to Bill. (e) * A girl dedicated and ate a pie to Bill. This first approximation is frought with difficulties. It ensures that constituents of like categories can be conjoined only if they share some finer details of specification, but there are more subtle conditions that it does not cover. For example, even though (5a) and (5b) are both independently grammatical, the coordination in (5c) is unacceptable: (5) (a) The girl promised John to go. (b) The girl persuaded John to go. (c) " " The girl promised and persuaded John to go, (Hint: Who is going "

Constituent

Coordination

Lexical-

Abstract

paper

outlines

theory

constituent

coordination

Lexical-

theory

arc

representation

constructions

Function-application

generalization

properties

structure

distributed

requiring

specifications

Introduction

treatment

coordination

goal

computational

approaches

language

formulation

terms

Reduction

rule

linguistic theories

Categorial grammar

progress

complex

restrictions

constructions

semantic interpretations

interpretations

Coordination

problems

computational

approaches

solved

devices

parsing

algorithms

constructions

rules

examples

kind

approach

Coordination

phenomena

classes

constituent

coordinations

constituents

coordination

fragments

constituents

verb

phrases

verbs

constituent

details

theory

theories

example

units

relations

rules

constituents

categorial grammars

order

combinations

motivation

lexical-functional

surface

constituents

units

interpretation

units

semantic interpretation

analysis

cross

dependencies

coordination

variety

complex

problems

constituent

coordination

issues

focus

paper

approximation

constituent

coordinations

result

clauses

common

verb

coordination

sentence

coordination

intuition

basis

Reduction

Transformation

complex

patterns

coordination

approximation

difficulties

constituents

categories

details

specification

example

coordination

paper

coordination

arc

constructions

semantic interpretations

constructions

devices

algorithms


Input: An Integrated Model For The Treatment Of Time In MT-Systems One of the ways to achieve a good translation of verbal foras is the morphosyntactic approach, which consists in a function pairing the different morphological tenses that occur in a given language with the tenses of the other language. Complicated rules must be established to calculate the right pair for an expression, because of the amount of discrepancies that different languages show with respect to each other. he way wa have chosen to deal with this problem is, conversely, the projection of the different values coming from verbs (type, processivity, morftense, morfaspect, sioodrequirement), from adverbs, prepositional phrases and temporal M.? s (deixis, aspect, iteration), and from subordinate conjunctions (aspect, moodrequirement). All this information permits to obtain a final value for aspect and tense for the whole sentence, which later on is percolated, not only to the verb node, but also to the the rest of elements conveying information. Our proposal relies on the fact that tense/aspect calculation is relevant not only for a good translation of verbs, but also for a good translation of adverbs, PPs, temporal Ni-n and conjunctions, as we have intended to demonstrate in this paper. I. Introduction Thin article deals with a methodology to achieve the right translation of temporal expressions by giving account of the temporal reference and temporal relations in/between sentences. The task to accomplish is to translate syntactic marks into semantic values that decide/reflect the aspectunl value of the sentences. For our treatment of time and aspect we draw on the work of Kamp [1979] and Partee [1984] who have argued for taking status and events as primitives and relations of precedence und overlapping between them. The ordering relation between events is crucial for deciding about the aspect of the sentences involved. The present proposal presumes an analysis and a generation component that deliver a set of S-trees whose leaves correspond to words. The pre-terminals have morphosyntatitic and relational information. As usual, features am percolated and nodes get features assigned. She tine/aspectual problem ia dealt with under the perspectiv of MT with the aim of sketching a system that can be implemented independently of the particular formalisms of different MT-systems. To outline a general model for the time/aspect calculation in MT we subsume a system with PSG rules that obtain some sentence structure with no regard to a specific grammar type; it could be an augmented PSG, as in METAL, or some kind of deep syntactic structure, as it is the case in Eurotra. The problem is the well known fact that translations of temporal expressions in Ni does not involve a simple mapping of tenses and adverbials. We could just compare Spanish, rich in aspect and tenses vs. German or English. That is, a MT dealing with Germanic and Romance languages is concerned with different parameters for each language; the whole practice in MT systems is to translate morphological tenses, and syntactical values into reference times that include events or slates

Model

Treatment

Time

MT-Systems

translation

verbal

approach

function

pairing

language

language

rules

pair

expression

amount

languages

respect

deal

problem

projection

verbs

type

adverbs

prepositional phrases

aspect

iteration

conjunctions

aspect

information

aspect

sentence

verb

node

information

proposal

aspect

calculation

translation

verbs

translation

adverbs

conjunctions

paper

Introduction

deals

methodology

translation

expressions

reference

temporal relations

sentences

task

translate

syntactic

semantic

sentences

treatment

time

aspect

status

events

relations

ordering

relation

events

aspect

sentences

proposal

analysis

generation

component

trees

words

relational

information

features

nodes

features

problem

dealt

system

implemented

formalisms

MT-systems

outline

model

time

aspect

calculation

system

rules

sentence structure

type

kind

syntactic structure

case

problem

translations

expressions

simple

mapping

aspect

English

dealing

languages

concerned

parameters

language

practice

MT systems

translate

reference

times

include

events

Model

Time

trees

words

features

nodes

translation

verbs

translation

adverbs

methodology

translation


Input: Improved Sentence Alignment on Parallel Web Pages Using a Stochastic Tree Alignment Model " Parallel web pages are important source of training data for statistical machine translation. In this paper, we present a new approach to sentence alignment on parallel web pages. Parallel web pages tend to have parallel structures, and the structural correspondence can be indicative information for identifying parallel sentences. In our approach, the web page is represented as a tree, and a stochastic tree alignment model is used to exploit the structural correspondence for sentence alignment. Experiments show that this method significantly enhances alignment accuracy and robustness for parallel web pages which are much more diverse and noisy than standard parallel corpora such as " " Hansard " ". With improved sentence alignment performance, web mining systems are able to acquire parallel sentences of higher quality from the web. "

Sentence

Alignment

Tree

Alignment Model

web pages

pages

source

training

data

statistical machine translation

paper

approach

sentence

alignment

web pages

pages

web pages

structures

structural

correspondence

information

sentences

approach

web page

page

tree

tree

alignment model

structural

correspondence

sentence

alignment

Experiments

method

alignment

accuracy

robustness

web pages

standard

parallel corpora

improved

sentence

alignment

performance

systems

sentences

quality

Alignment

Sentence

alignment

web pages

data

web pages

paper

approach

tree

web page

method

accuracy

systems

quality


Input: A Japanese Predicate Argument Structure Analysis using Decision Lists This paper describes a new automatic method for Japanese predicate argument structure analysis. The method learns relevant features to assign case roles to the argument of the target predicate using the features of the words located closest to the target predicate under various constraints such as dependency types, words, semantic categories, parts of speech, functional words and predicate voices. We constructed decision lists in which these features were sorted by their learned weights. Using our method, we integrated the tasks of semantic role labeling and zero-pronoun identification, and achieved a 17% improvement compared with a baseline method in a sentence level performance analysis.

Japanese

Predicate Argument Structure

Analysis

Decision

paper

automatic

method

Japanese

predicate argument structure

argument structure

analysis

method

features

case

roles

argument

target

features

words

target

constraints

dependency

types

words

semantic

categories

parts of speech

words

constructed

decision

lists

features

weights

method

tasks

semantic role

identification

improvement

method

sentence level

performance

analysis

paper

method

analysis

predicate argument structure


Input: Joint Unsupervised Coreference Resolution with Markov Logic Machine learning approaches to coreference resolution are typically supervised, and require expensive labeled data. Some unsuper-vised approaches have been proposed (e. g., Haghighi and Klein (2007)), but they are less accurate. In this paper, we present the first un-supervised approach that is competitive with supervised ones. This is made possible by performing joint inference across mentions, in contrast to the pairwise classification typically used in supervised methods, and by using Markov logic as a representation language, which enables us to easily express relations like apposition and predicate nominals. On MUC and ACE datasets, our model outperforms Haghigi and Klein' s one using only a fraction of the training data, and often matches or exceeds the accuracy of state-of-the-art supervised models.

Coreference Resolution

Logic

Machine

approaches

coreference resolution

require

data

approaches

proposed

paper

approach

performing

inference

mentions

contrast

classification

methods

logic

representation language

relations

ACE

model

training

matches

accuracy

models

paper

approach


Input: The GENIA Project: Corpus-Based Knowledge Acquisition And Information Extraction From Genome Research Papers We present an outline of the genome information acquisition (GENIA) project for automatically extracting biochemical information from journal papers and abstracts. GENIA will be available over the Internet and is designed to aid in information extraction, retrieval and visualisation and to help reduce information overload on researchers. The vast repository of papers available online in databases such as MEDLINE is a natural environment in which to develop language engineering methods and tools and is an opportunity to show how language engineering can play a key role on the Internet.

Project

Corpus-

Based

Knowledge

Acquisition

Information Extraction

Research

Papers

outline

information

acquisition

project

extracting

information

journal

papers

abstracts

designed

information extraction

retrieval

help

information

researchers

repository

papers

databases

natural

environment

develop

language

engineering

methods

tools

language

engineering

role

information

papers

papers

databases


Input: Interactive Word Alignment For Language Engineering In this paper we report ongoing work on developing an interactive word alignment environment that will assist a user to quickly produce accurate full-coverage word alignment in bitexts for different language engineering tasks, such as MT lexicons and gold standards for evaluation. The system uses a graphical interface, static and dynamic resources as well as machine learning techniques. We also sketch how the system is being integrated with an automatic word aligner.

Word Alignment

Language

Engineering

paper

report

developing

word alignment

alignment

environment

user

full-coverage

word alignment

language

engineering

tasks

lexicons

gold standards

standards

evaluation

system

interface

resources

machine

techniques

system

automatic

word

paper

word alignment

gold standards

evaluation


Input: Re-Evaluation The Role Of Bleu In Machine Translation Research We argue that the machine translation community is overly reliant on the Bleu machine translation evaluation metric. We show that an improved Bleu score is neither necessary nor sufficient for achieving an actual improvement in translation quality, and give two significant counterexamples to Bleu' s correlation with human judgments of quality. This offers new potential for research which was previously deemed unpromising by an inability to improve upon Bleu scores.

Evaluation

Role

Machine Translation

Research

machine translation

community

translation

evaluation metric

metric

improved

improvement

translation quality

quality

correlation

judgments

quality

research

inability

improve

evaluation metric

translation


Input: Automatically Constructing A Lexicon Of Verb Phrase Idiomatic Combinations We investigate the lexical and syntactic flexibility of a class of idiomatic expressions. We develop measures that draw on such linguistic properties, and demonstrate that these statistical, corpus-based measures can be successfully used for distinguishing idiomatic combinations from non-idiomatic ones. We also propose a means for automatically determining which syntactic forms a particular idiom can appear in, and hence should be included in its lexical representation.

Lexicon

Verb

Phrase

lexical

syntactic

flexibility

class

expressions

develop

properties

statistical

corpus-based

combinations

propose

syntactic

forms

idiom

included

lexical

representation

expressions

class

representation

idiom


Input: An Education And Research Tool For Computational Semantics This paper describes an interactive graphical environment for computational semantics. The system provides a teaching tool, a stand alone extendible grapher, and a library of algorithms together with test suites. The teaching tool allows users to work step by step through derivations of semantic representations, and to compare the properties of various semantic formalisms such as Intensional Logic, DRT, and Situation Semantics. The system is freely available on the Internet.

Research

Tool

Computational

Semantics

paper

environment

computational

semantics

system

provides

tool

library

algorithms

test suites

tool

users

step

step

derivations

semantic representations

properties

semantic

formalisms

Logic

Situation

Semantics

system

Tool

Semantics

library

algorithms


Input: The Effects Of Word Order And Segmentation On Translation Retrieval Performance This research looks at the effects of word order and segmentation on translation retrieval performance for an experimental Japanese-English translation memory system. We implement a number of both bag-of-words and word order-sensitive similarity metrics, and test each over character-based and word-based indexing. The translation retrieval performance of each system configuration is evaluated empirically through the notion of word edit distance between translation candidate outputs and the model translation. Our results indicate that character-based indexing is consistently superior to word-based indexing, suggesting that segmentation is an unnecessary luxury in the given domain. Word order-sensitive approaches are demonstrated to generally outperform bag-of-words methods, with source language segment-level edit distance proving the most effective similarity metric.

Word

Order

Translation

Retrieval

Performance

research

effects

word

order

translation

retrieval

performance

experimental

Japanese-

English

translation

memory

system

implement

number

bag-of-words

word

order-sensitive

similarity

metrics

test

word-based

indexing

translation

retrieval

performance

system

configuration

evaluated

notion

word

distance

translation

candidate

outputs

model

translation

results

indexing

word-based

indexing

domain

Word

order-sensitive

approaches

bag-of-words

methods

source language

segment-level

distance

similarity

metric

order-sensitive

bag-of-words


Input: Reusing An Ontology To Generate Numeral Classifiers In this paper, we present a solution to the problem of generating Japanese numeral classifiers using semantic classes from an ontology. Most nouns must take a numeral classifier when they are quantified in languages such as Chinese, Japanese, Korean, Malay and Thai. In order to select an appropriate classifier, we propose an algorithm which associates classifiers with semantic classes and uses inheritance to list only those classifiers which have to be listed. It generates sortal classifiers with an accuracy of 81%. We reuse the ontology provided by Goi-Taikei a Japanese lexicon, and show that it is a reasonable choice for this task, requiring information to be entered for less than 6% of individual nouns.

Ontology

Generate

paper

solution

problem

generating

Japanese

classifiers

semantic classes

classes

ontology

nouns

classifier

languages

Chinese

Japanese

order

classifier

propose

algorithm

classifiers

semantic classes

list

classifiers

listed

generates

classifiers

accuracy

ontology

provided

Japanese

lexicon

choice

task

requiring

information

individual

nouns

semantic classes

classifiers


Input: Aspects Of Pattern-Matching In Data-Oriented Parsing Data-Oriented Parsing (dop) ranks among the best parsing schemes, pairing state-of-the art parsing accuracy to the psycholinguistic insight that larger chunks of syntactic structures are relevant grammatical and probabilistic units. Parsing with the dop-model, however, seems to involve a lot of CPU cycles and a considerable amount of double work, brought on by the concept of multiple derivations, which is necessary for probabilistic processing, but which is not convincingly related to a proper linguistic backbone. It is however possible to reinterpret the dop-model as a pattern-matching model, which tries to maximize the size of the substructures that construct the parse, rather than the probability of the parse. By emphasizing this memory-based aspect of the dop-model, it is possible to do away with multiple derivations, opening up possibilities for efficient Viterbi-style optimizations, while still retaining acceptable parsing accuracy through enhanced context-sensitivity.

Pattern-

Data-

Parsing

Data-

Parsing

ranks

parsing

schemes

pairing

parsing

accuracy

insight

chunks

syntactic structures

units

Parsing

dop-model

cycles

amount

concept

derivations

processing

backbone

dop-model

pattern-matching

model

size

substructures

construct

parse

probability

parse

memory-based

aspect

dop-model

derivations

possibilities

optimizations

parsing

accuracy

context-sensitivity

substructures

parse


Input: A Hybrid Japanese Parser With Hand-Crafted Grammar And Statistics This paper describes a hybrid parsing method for Japanese which uses both a hand-crafted grammar and a statistical technique. The key feature of our system is that in order to estimate likelihood for a parse tree, the system uses information taken from alternative partial parse trees generated by the grammar. This utilization of alternative trees enables us to construct a new statistical model called Triplet/Quadruplet Model. We

Japanese

Parser

Hand-

Statistics

paper

parsing

method

Japanese

hand-crafted

statistical

technique

feature

system

order

parse tree

system

information

alternative

partial

parse trees

trees

generated

alternative

trees

construct

statistical model

called

Model

paper

method

information

parse trees


Input: Learning Semantic-Level Information Extraction Rules By Type-Oriented ILP This paper describes an approach to using semantic representations information extraction (IE) inductive logic programming (ILP)

Learning

Semantic-

Level

Information Extraction

Type-

paper

approach

semantic representations

information extraction

logic programming

paper

approach


Input: Robust German Noun Chunking With A Probabilistic Context-Free Grammar We present a noun chunker for German which is based on a head-lexicalised probabilistic context-free grammar. A manually developed grammar was semi-automatically extended with robustness rules in order to allow parsing of unrestricted text. The model parameters were learned from unlabelled training data by a probabilistic context-free parser. For extracting noun chunks, the parser generates all possible noun chunk analyses, scores them with a novel algorithm which maximizes the best chunk sequence criterion, and chooses the most probable chunk sequence. An evaluation of the chunker on 2, 140 hand-annotated noun chunks yielded 92% recall and 93% precision.

Robust

Noun

Context-

noun

based

context-free

developed

robustness

rules

order

parsing

text

model parameters

parameters

training

data

context-free

parser

extracting

noun

chunks

parser

generates

noun

chunk

analyses

algorithm

chunk

sequence

criterion

chunk

sequence

evaluation

hand-annotated

noun

chunks

yielded

recall

precision

rules

parsing

model parameters

data


Input: The Week At A Glance-Cross-Language Cross-Document Information Extraction And Translation " Work on the production of texts in English describing instances of a particular event type from multiple news sources will be described. A system has been developed which extracts events, such as meetings, from texts in English, Russian, Spanish, and Japanese. The extraction is currently carried out using only ontological information. The results of a set of such extractions were combined to produce a table of event instances, date stamped, with links back to the original documents. The original documents can then be summarized and translated by the system on demand. By using techniques from information retrieval, information extraction, summarization, and machine translation, in a multi-lingual environment, new documents can be produced which provide " " at a glance " " access to news on events from multiple sources. The paper concludes with a discussion of the key resources which need to be developed to enhance the accuracy and coverage of the techniques used in our experiment. "

Cross-

Language

Cross-

Document

Information Extraction

Translation

texts

English

instances

event type

news

sources

system

developed

extracts

events

meetings

texts

English

Japanese

extraction

information

results

extractions

table

event

instances

date

links

documents

documents

translated

system

techniques

information retrieval

information extraction

summarization

machine translation

multi-lingual

environment

documents

provide

access

news

events

sources

paper

discussion

resources

developed

accuracy

coverage

techniques

experiment


Input: Querying Temporal Databases Using Controlled Natural Language Recent years have shown a surge in interest in temporal database systems, which allow users to store time-dependent information. We present a novel controlled natural language interface to temporal databases, based on translating natural language questions into SQL/Temporal, a temporal database query language. The syntactic analysis is done using the Type-Logical Grammar framework, highlighting its utility not only as a theoretical framework but also as a practical tool. The semantic analysis is done using a novel theory of the semantics of temporal questions, focusing on the role of temporal preposition phrases rather than the more traditional focus on tense and aspect. Our translation method is considerably simpler than previous attempts in this direction. We present a prototype software implementation.

Natural Language

database

systems

users

time-dependent

information

natural language interface

databases

based

translating

natural language

questions

query language

syntactic analysis

analysis

Type-

framework

utility

framework

tool

semantic analysis

analysis

theory

semantics

questions

focusing

role

preposition

phrases

focus

aspect

translation

method

direction

prototype

software

implementation

framework

syntactic analysis

theory

semantic analysis


Input: Learning Chinese Bracketing Knowledge Based On A Bilingual Language Model This paper proposes a new method for automatic acquisition of Chinese bracketing knowledge from English-Chinese sentence-aligned bilingual corpora. Bilingual sentence pairs are first aligned in syntactic structure by combining English parse trees with a statistical bilingual language model. Chinese bracketing knowledge is then extracted automatically. The preliminary experiments show automatically learned knowledge accords well with manually annotated brackets. The proposed method is particularly useful to acquire bracketing knowledge for a less studied language that lacks tools and resources found in a second language more studied. Although this paper discusses experiments with Chinese and English, the method is also applicable to other language pairs.

Learning

Chinese

Bracketing

Knowledge Based

Language Model

paper

proposes

method

automatic

acquisition

Chinese

bracketing

knowledge

English-

Chinese

sentence-aligned

corpora

sentence

pairs

syntactic structure

English

parse trees

statistical

language model

Chinese

bracketing

knowledge

extracted

experiments

knowledge

brackets

proposed

method

bracketing

knowledge

studied

language

lacks

tools

resources

second language

studied

paper

experiments

Chinese

English

method

language pairs

pairs

paper

method

knowledge

corpora

method

language pairs


Input: The Computation Of Word Associations: Comparing Syntagmatic And Paradigmatic Approaches It is shown that basic language processes such as the production of free word associations and the generation of synonyms can be simulated using statistical models that analyze the distribution of words in large text corpora. According to the law of association by contiguity, the acquisition of word associations can be explained by Hebbian learning. The free word associations as produced by subjects on presentation of single stimulus words can thus be predicted by applying first-order statistics to the frequencies of word co-occurrences as observed in texts. The generation of synonyms can also be conducted on co-occurrence data but requires second-order statistics. The reason is that synonyms rarely occur together but appear in similar lexical neighborhoods. Both approaches are systematically compared and are validated on empirical data. It turns out that for both tasks the performance of the statistical system is comparable to the performance of human subjects.

Computation

Word

Approaches

basic

language

processes

word

associations

generation

synonyms

statistical models

models

distribution

words

text

corpora

association

acquisition

word

associations

word

associations

presentation

stimulus

words

applying

first-order

statistics

frequencies

word

texts

generation

synonyms

co-occurrence

data

requires

second-order

statistics

reason

synonyms

lexical

approaches

data

tasks

performance

statistical

system

performance

statistical models

corpora

performance

performance


Input: A Chart-Parsing Algorithm For Efficient Semantic Analysis " In some contexts, well-formed natural language cannot be expected as input to information or communication systems. In these contexts, the use of grammar-independent input (sequences of uninflected semantic units like e. g. language-independent icons) can be an answer to the users' needs. However, this requires that an intelligent system should be able to interpret this input with reasonable accuracy and in reasonable time. Here we propose a method allowing a purely semantic-based analysis of sequences of semantic units. It uses an algorithm inspired by the idea of " " chart parsing " " known in Natural Language Processing, which stores intermediate parsing results in order to bring the calculation time down. "

Parsing Algorithm

Algorithm

Semantic Analysis

Analysis

contexts

natural language

input

information

communication

systems

contexts

input

sequences

semantic

units

language-independent

icons

users

requires

system

input

accuracy

time

propose

method

semantic-based

analysis

sequences

semantic

units

algorithm

parsing

Natural Language Processing

parsing

results

order

calculation

time

Parsing Algorithm

Semantic Analysis

analysis

sequences


Input: A Generative Probability Model For Unification-Based Grammars A generative probability model for unification-based grammars is presented in which rule probabilities depend on the feature structure of the expanded constituent. The presented model is the first model which requires no normalization and allows the application of dynamic programming algorithms for disambiguation (Viterbi) and training (Inside-Outside). Another advantage is the small number of parameters.

Probability Model

Unification-

Based

probability model

unification-based

rule

probabilities

feature structure

constituent

model

model

requires

normalization

application

dynamic programming algorithms

programming

algorithms

disambiguation

training

advantage

number

parameters

dynamic programming algorithms

disambiguation


Input: Augmenting Noun Taxonomies By Combining Lexical Similarity Metrics This paper presents a method for augmenting taxonomies with domain information using a simple combination of three existing lexical similarity metrics. The combined approach is evaluated by comparing their results against the annotated SEMCOR corpus. An implementation is described in which WordNet is augmented with thesaural information from the CIDE + machine readable dictionary.

Noun

Combining

Lexical

Similarity

paper

method

taxonomies

domain

information

simple

combination

lexical

similarity

metrics

approach

evaluated

results

corpus

implementation

information

machine readable dictionary

paper

method


Input: A Method Of Cluster-Based Indexing Of Textual Data This paper presents a framework for clustering in text-based information retrieval systems. The prominent feature of the proposed method is that documents, terms, and other related elements of textual information are clustered simultaneously into small overlapping clusters. In the paper, the mathematical formulation and implementation of the clustering method are briefly introduced, together with some experimental results.

Method

Cluster-

Based

Indexing

Data

paper

framework

clustering

text-based

information retrieval systems

feature

proposed

method

documents

terms

information

clustered

clusters

paper

formulation

implementation

clustering

method

experimental

results

Indexing

Data

paper

framework


Input: Processing Japanese Self-Correction In Speech Dialog Systems Speech dialog systems need to deal with various kinds of ill-formed speech inputs that appear in natural human-human dialog. Self-correction (or speech-repair) is a particularly problematic phenomenon. Although many ways of dealing with self-correction have been proposed, these have limitations in both detecting and correcting for this phenomenon. In this paper, we propose a method to overcome these problems in Japanese speech dialog. We evaluate the proposed method using our speech dialog corpus and discuss its limitations and the work that remains to be done.

Processing

Japanese

Correction

Speech

Dialog

Systems

Speech

dialog systems

deal

kinds

speech

inputs

natural

dialog

Self-correction

speech-repair

phenomenon

dealing

self-correction

proposed

limitations

phenomenon

paper

propose

method

problems

Japanese

speech

dialog

evaluate

proposed

method

speech

dialog

corpus

limitations

paper

method


Input: Fertilization Of Case Frame Dictionary For Robust Japanese Case Analysis This paper proposes a method of fertilizing a Japanese case frame dictionary to handle complicated expressions: double nominative sentences, non-gapping relation of relative clauses, and case change. Our method is divided into two stages. In the first stage, we parse a large corpus and construct a Japanese case frame dictionary automatically from the parse results. In the second stage, we apply case analysis to the large corpus utilizing the constructed case frame dictionary, and upgrade the case frame dictionary by incorporating newly acquired information.

Case

Frame

Dictionary

Robust

Japanese

Case

Analysis

paper

proposes

method

Japanese

case

frame

dictionary

expressions

sentences

relation

relative

clauses

case

method

parse

corpus

construct

Japanese

case

frame

dictionary

parse

results

apply

case

analysis

corpus

constructed

case

frame

dictionary

case

frame

dictionary

information

paper

method


Input: Open-Domain Voice-Activated Question Answering Voice-Activated Question Answering (VAQA) systems represent the next generation capability for universal access by integrating state-of-the-art in question answering Q & A and automatic speech recognition (ASR) in such a way that the performance of the combined system is better than the individual components. This paper presents an implemented VAQA system and describes the techniques that enable the terative refinement of both Q & A and ASR. The results of our experiments show that spoken questions can be processed with surprising accuracy when using our VAQA implementation.

Domain

Question Answering

Question Answering

systems

generation

capability

access

question

automatic speech recognition

performance

system

individual

components

paper

implemented

system

techniques

refinement

results

experiments

questions

processed

accuracy

implementation

system

components

paper

system


Input: Generating Discourse Structures For Written Text This paper presents a system for automatically generating discourse structures from written text. The system is divided into two levels: sentence-level and text-level. The sentence-level discourse parser uses syntactic information and cue phrases to segment sentences into elementary discourse units and to generate discourse structures of sentences. At the text-level, constraints about textual adjacency and textual organization are integrated in a beam search in order to generate best discourse structures. The experiments were done with documents from the RST Discourse Treebank. It shows promising results in a reasonable search space compared to the discourse trees generated by human analysts.

Generating

Discourse

Structures

Text

paper

system

generating

discourse structures

text

system

levels

sentence-level

text-level

sentence-level

discourse

parser

syntactic information

cue

phrases

segment

sentences

discourse

units

generate

discourse structures

sentences

text-level

constraints

organization

beam search

order

generate

discourse structures

experiments

documents

Discourse

results

search space

discourse

trees

generated

analysts

paper

system


Input: Improving Japanese Zero Pronoun Resolution By Global Word Sense Disambiguation This paper proposes unsupervised word sense disambiguation based on automatically constructed case frames and its incorporation into our zero pronoun resolution system. The word sense disambiguation is applied to verbs and nouns. We consider that case frames define verb senses and semantic features in a thesaurus define noun senses, respectively, and perform sense disambiguation by selecting them based on case analysis. In addition, according to the one sense per discourse heuristic, the word sense disambiguation results are cached and applied globally to the subsequent words. We integrated this global word sense disambiguation into our zero pronoun resolution system, and conducted experiments of zero pronoun resolution on two different domain corpora. Both of the experimental results indicated the effectiveness of our approach.

Japanese

Resolution

Word Sense Disambiguation

paper

proposes

word sense disambiguation

based

constructed

case

frames

resolution

system

word sense disambiguation

sense disambiguation

applied

verbs

nouns

case

frames

verb

semantic features

thesaurus

noun

perform

sense disambiguation

based

case

analysis

addition

sense

discourse

word sense disambiguation

results

applied

words

word sense disambiguation

resolution

system

experiments

resolution

domain

corpora

experimental

results

effectiveness

approach

paper

system

word sense disambiguation

verbs

approach

results


Input: BiFrameNet: Bilingual Frame Semantics Resource Construction By Cross-Lingual Induction " We present a novel automatic approach to constructing a bilingual semantic network the BiFrameNet, to enhance statistical and transfer-based machine translation systems. BiFrameNet is a frame semantic representation, and contains semantic structure transfers between English and Chinese. The English FrameNet and the Chinese HowNet provide us with two different views of the semantic distribution of lexicon by linguists. We propose to induce the mapping between the English lexical entries in FrameNet to Chinese word senses in HowNet, furnishing a bilingual semantic lexicon which simulates the " " concept lexicon " " supposedly used by human translators, and which can thus be beneficial to machine translation systems. BiFrameNet also contains bilingual example sentences that have the same semantic roles. We automatically induce Chinese example sentences and their semantic roles, based on semantic structure alignment from the first stage of our work, as well as shallow syntactic structure. In addition to its utility for machine-aided and machine translations, our work is also related to the spatial models proposed by cognitive scientists in the framework of artifactual simulations of the translation process. "

Frame

Semantics

Resource

Construction

Cross-

Lingual

Induction

automatic

approach

constructing

semantic network

statistical

transfer-based

machine translation systems

frame

semantic representation

semantic structure

transfers

English

Chinese

English

Chinese

provide

semantic

distribution

lexicon

linguists

propose

mapping

English

lexical entries

Chinese

word

semantic lexicon

concept

lexicon

translators

machine translation systems

example

sentences

semantic roles

Chinese

example

sentences

semantic roles

based

semantic structure

structure

alignment

syntactic structure

structure

addition

utility

machine-aided

machine translations

models

proposed

scientists

framework

simulations

translation process


Input: A Computational Theory Of Prose Style For Natural Language Generation " 1. Where in the generation process style is taken into account. 2. How a particular prose style is represented; what " " stylistic rules " " look like; 3. What modifications to a generation algorithm are needed; what the decision is that evaluates stylistic alternatives; 4. What elaborations to the normal description of surface structure are necessary to make it usable as a plan for the text and a reference for these decisions; 5. What kinds of information decisions about style have access to. Our theory emerged out of design experiments we have made over the past year with our natural language generation system, the Zetalisp program MUMBLE. In the process we have extended MUMBLE through the addition of an additional process that now mediates between content planning and linguistic realization. This new process, which we call " " attachment " ", provides the further significant benefit that text structure is no longer dictated by the structure of the message: the sequential order and dominance relationships of concepts in the message no longer force one form onto the words and phrases in the text. Instead, rhetorical and intentional directives can be interpreted flexibly in the context of the ongoing discourse and stylistic preferences. The text is built up through composition under the direction of linguistic organizing principles, rather than having to follow conceptual principles in lockstep. We will begin by describing what we mean by prose style and then introducing the generation task that lead us to this theory, the reproduction of short encyclopedia articles on African tribes. We will then use that task to outline the parts of our theory and the operations of the attachment process. Finally we will compare our techniques to the related work of Davey, McKeown and Derr, and Gabriel, and consider some of the possible psycholinguistic hypotheses that it may lead to. "

Computational

Theory

Natural Language Generation

Language Generation

generation process

rules

modifications

generation

algorithm

decision

evaluates

alternatives

description

surface structure

text

reference

decisions

kinds

information

decisions

access

theory

design

experiments

natural language generation system

program

process

addition

process

content

realization

process

call

attachment

provides

benefit

text structure

structure

message

order

relationships

concepts

message

form

words

phrases

text

context

discourse

preferences

text

direction

principles

principles

generation

task

theory

encyclopedia

task

outline

parts

theory

operations

attachment

process

techniques

hypotheses

Theory

Natural Language Generation


Input: Prediction In Chart Parsing Algorithms For Categorial Unification Grammar Natural language systems based on Categorial Unification Grammar (CUG) have mainly employed bottom-up parsing algorithms for processing. Conventional prediction techniques to improve the efficiency of the parsing process, appear to fall short when parsing CUG. Nevertheless, prediction seems necessary when parsing grammars with highly ambiguous lexicons or with non-canonical categorial rules. In this paper we present a lexicalist prediction technique for CUG and show that this may lead to considerable gains in efficiency for both bottom-up and top-down parsing.

Prediction

Parsing

Algorithms

Unification

Natural language systems

based

Unification

parsing

algorithms

processing

prediction

techniques

improve

efficiency

parsing

process

parsing

prediction

parsing

lexicons

rules

paper

prediction

technique

gains

efficiency

parsing

paper

technique