Automatic ambiguity resolution in natural language processing: an empirical approach
Gespeichert in:
| 1. Verfasser: | |
|---|---|
| Format: | Buch |
| Sprache: | English |
| Veröffentlicht: |
Berlin u.a.
Springer
1996
|
| Schriftenreihe: | Lecture notes in computer science
1171 : Lecture notes in artificial intelligence |
| Schlagworte: | |
| Online-Zugang: | Inhaltsverzeichnis |
| Beschreibung: | XV, 155 S. graph. Darst. |
| ISBN: | 3540620044 |
Internformat
MARC
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| 001 | BV011034940 | ||
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| 084 | |a DAT 710f |2 stub | ||
| 084 | |a 28 |2 sdnb | ||
| 100 | 1 | |a Franz, Alexander |e Verfasser |4 aut | |
| 245 | 1 | 0 | |a Automatic ambiguity resolution in natural language processing |b an empirical approach |c Alexander Franz |
| 264 | 1 | |a Berlin u.a. |b Springer |c 1996 | |
| 300 | |a XV, 155 S. |b graph. Darst. | ||
| 336 | |b txt |2 rdacontent | ||
| 337 | |b n |2 rdamedia | ||
| 338 | |b nc |2 rdacarrier | ||
| 490 | 1 | |a Lecture notes in computer science |v 1171 : Lecture notes in artificial intelligence | |
| 650 | 4 | |a Natural language processing (Computer science) | |
| 650 | 4 | |a Ambiguity | |
| 650 | 0 | 7 | |a Natürlichsprachiges System |0 (DE-588)4284757-6 |2 gnd |9 rswk-swf |
| 650 | 0 | 7 | |a Natürliche Sprache |0 (DE-588)4041354-8 |2 gnd |9 rswk-swf |
| 650 | 0 | 7 | |a Syntaktische Analyse |0 (DE-588)4058778-2 |2 gnd |9 rswk-swf |
| 650 | 0 | 7 | |a Ambiguität |0 (DE-588)4138525-1 |2 gnd |9 rswk-swf |
| 650 | 0 | 7 | |a Sprachverarbeitung |0 (DE-588)4116579-2 |2 gnd |9 rswk-swf |
| 689 | 0 | 0 | |a Ambiguität |0 (DE-588)4138525-1 |D s |
| 689 | 0 | 1 | |a Natürlichsprachiges System |0 (DE-588)4284757-6 |D s |
| 689 | 0 | |5 DE-604 | |
| 689 | 1 | 0 | |a Natürliche Sprache |0 (DE-588)4041354-8 |D s |
| 689 | 1 | 1 | |a Sprachverarbeitung |0 (DE-588)4116579-2 |D s |
| 689 | 1 | 2 | |a Ambiguität |0 (DE-588)4138525-1 |D s |
| 689 | 1 | 3 | |a Syntaktische Analyse |0 (DE-588)4058778-2 |D s |
| 689 | 1 | |5 DE-604 | |
| 830 | 0 | |a Lecture notes in computer science |v 1171 : Lecture notes in artificial intelligence |w (DE-604)BV000000607 |9 1171 | |
| 856 | 4 | 2 | |m DNB Datenaustausch |q application/pdf |u http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=007389621&sequence=000001&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA |3 Inhaltsverzeichnis |
| 943 | 1 | |a oai:aleph.bib-bvb.de:BVB01-007389621 | |
Datensatz im Suchindex
| _version_ | 1807773663136579584 |
|---|---|
| adam_text |
TABLE
OF
CONTENTS
1.
INTRODUCTION
.
1
1.1
NATURAL
LANGUAGE
AMBIGUITY
.
2
1.2
AMBIGUITY
AND
ROBUST
PARSING
.
3
1.2.1
GRAMMATICAL
COVERAGE
.
4
1.2.2
AMBIGUITY
RESOLUTION
SCHEMES
.
5
1.3
CORPUS-BASED
APPROACHES
TO
NLP
.
6
1.3.1
EMPIRICAL
ORIENTATION
.
6
1.3.2
NATURALLY-OCCURRING
LANGUAGE
.
7
1.3.3
EMPHASIS
ON
EVALUATION
.
7
1.4
STATISTICAL
MODELING
FOR
AMBIGUITY
RESOLUTION
.
8
1.5
OVERVIEW
OF
THIS
BOOK
.
8
2.
PREVIOUS
WORK
ON
SYNTACTIC
AMBIGUITY
RESOLUTION
.
11
2.1
A
NOTE
ON
REPORTED
ERROR
RATES
.
11
2.2
THE
PROBLEM
OF
UNKNOWN
WORDS
.
11
2.2.1
AI
APPROACHES
TO
UNKNOWN
WORDS
.
12
2.2.2
MORPHOLOGICAL
ANALYSIS
OF
UNKNOWN
WORDS
.
12
2.2.3
CORPUS-BASED
APPROACHES
TO
UNKNOWN
WORDS
.
13
2.3
LEXICAL
SYNTACTIC
AMBIGUITY
.
13
2.3.1
RULE-BASED
LEXICAL
SYNTACTIC
AMBIGUITY
RESOLUTION.
.
13
2.3.2
FREQUENCY-BASED
POS
TAGGING
.
14
2.3.3
HIDDEN
MARKOV
MODELS
FOR
LEXICAL
DISAMBIGUATION
.
16
2.3.4
N-GRAM
BASED
STOCHASTIC
POS
TAGGING
.
17
2.4
STRUCTURAL
AMBIGUITY
.
19
2.4.1
SYNTACTIC
APPROACHES
.
19
2.4.2
SEMANTIC
APPROACHES
.
20
2.4.3
PRAGMATIC
APPROACHES
.
22
2.5
PREPOSITIONAL
PHRASE
ATTACHMENT
DISAMBIGUATION
.
23
2.5.1
USING
LEXICAL
ASSOCIATIONS
FOR
PP
ATTACHMENT
DISAM
BIGUATION
.
27
2.5.2
SYSTEMATIC
AMBIGUITY
IN
PP
ATTACHMENT
.
28
2.5.3
PP
ATTACHMENT
AND
CLASS-BASED
GENERALIZATION
.
28
2.5.4 A
MAXIMUM
ENTROPY
MODEL
OF
PP
ATTACHMENT
.
29
2.5.5
LEARNING
SYMBOLIC
PP
ATTACHMENT
RULES
.
30
XII
TABLE
OF
CONTENTS
2.6
CRITIQUE
OF
PREVIOUS
APPROACHES
.
30
2.6.1
SYNTACTIC
APPROACHES
.
31
2.6.2
SEMANTIC
AND
PRAGMATIC
APPROACHES
.
31
2.6.3
CORPUS-BASED
APPROACHES
.
32
3.
LOGLINEAR
MODELS
FOR
AMBIGUITY
RESOLUTION
.
35
3.1
REQUIREMENTS
FOR
EFFECTIVE
AMBIGUITY
RESOLUTION
.
35
3.1.1
AUTOMATIC
TRAINING
.
35
3.1.2
HANDLING
MULTIPLE
FEATURES
.
35
3.1.3
MODELING
FEATURE
DEPENDENCIES
.
36
3.1.4
ROBUSTNESS
.
36
3.2
AMBIGUITY
RESOLUTION
AS
A
CLASSIFICATION
PROBLEM
.
36
3.2.1
MAKING
DECISIONS
UNDER
UNCERTAINTY
.
36
3.2.2
STATISTICAL
CLASSIFICATION
.
37
3.2.3
EXPECTED
LOSS
AND
THE
ZERO-ONE
LOSS
FUNCTION
.
38
3.2.4
MINIMUM
ERROR
RATE
CLASSIFICATION
.
38
3.2.5
MAXIMIZING
UTILITY
.
39
3.3
THE
LOGLINEAR
MODEL
.
40
3.3.1
CATEGORICAL
DATA
ANALYSIS
.
40
3.3.2
THE
CONTINGENCY
TABLE
.
40
3.3.3
THE
IMPORTANCE
OF
SMOOTHING
.
41
3.3.4
INDIVIDUAL
CELLS
.
42
3.3.5
MARGINAL
TOTALS
AND
EXPECTED
CELL
COUNTS
.
42
3.3.6
INTERDEPENDENT
VARIABLES
AND
INTERACTION
TERMS
.
43
3.3.7
THE
ITERATIVE
ESTIMATION
PROCEDURE
.
44
3.3.8
EXAMPLE
OF
ITERATIVE
ESTIMATION
.
45
3.3.9
DEFINITION
OF
A
LOGLINEAR
MODEL
.
46
3.4
STATISTICAL
INFERENCE
.
47
3.4.1
THE
BAYESIAN
APPROACH
.
47
3.4.2
BAYESIAN
INFERENCE
USING
THE
CONTINGENCY
TABLE
.
47
3.5
EXPLORATORY
DATA
ANALYSIS
.
48
3.5.1
THE
EXPLORATORY
NATURE
OF
THIS
APPROACH
.
48
3.5.2
SEARCHING
FOR
DISCRIMINATORS
.
49
4.
MODELING
NEW
WORDS
.
51
4.1
EXPERIMENTAL
DATA
AND
PROCEDURE
.
51
4.1.1
PROBLEM
STATEMENT
.
51
4.1.2
EXPERIMENTAL
DATA
.
51
4.1.3
MODELING
PROCEDURE
.
53
4.2
EXPLORING
THE
DATA
.
53
4.2.1
THE
INITIAL
FEATURE
SET
.
53
4.2.2
DECREASING
THE
SIZE
OF
THE
MODEL
.
54
4.2.3
ELIMINATING
LOW-INFORMATION
FEATURES
.
55
4.2.4
CHOOSING
THE
INTERACTION
TERMS
.
57
4.3
EVALUATION
AND
EXPERIMENTAL
RESULTS
.
59
TABLE
OF
CONTENTS
XIII
4.3.1
MEASURING
RESIDUAL
AMBIGUITY:
AN
EXAMPLE
.
60
4.3.2
RESULTS
FROM
PREVIOUS
WORK
.
62
4.3.3
CONSTRUCTING
THE
LOGLINEAR
MODEL
.
63
4.3.4
EXPERIMENTAL
RESULTS
.
66
4.3.5
EFFECT
OF
NUMBER
OF
FEATURES
ON
PERFORMANCE
.
67
4.3.6
NUMBER
OF
FEATURES
AND
RESIDUAL
AMBIGUITY
.
68
4.3.7
THE
TRADEOFF
BETWEEN
ACCURACY
AND
AMBIGUITY
.
69
5.
PART-OF-SPEECH
AMBIGUITY
.
71
5.1
STOCHASTIC
PART-OF-SPEECH
TAGGING
.
71
5.1.1
MAXIMIZING
TAG
SEQUENCE
PROBABILITY
.
71
5.1.2
MAKING
INDEPENDENCE
ASSUMPTIONS
.
72
5.1.3
THE
TAGGING
ALGORITHM
.
-
73
5.2
ESTIMATION
OF
PROBABILITIES
.
74
5.2.1
TAGGED
VERSUS
UNTAGGED
TRAINING
CORPORA
.
74
5.2.2
JEFFREYS
'
ESTIMATE
.
74
5.2.3
LINEAR
INTERPOLATION
.
75
5.2.4
DELETED
INTERPOLATION
.
76
5.2.5
OTHER
SMOOTHING
SCHEMES
.
77
5.3
STOCHASTIC
TAGGING
WITH
UNKNOWN
WORDS
.
77
5.3.1
EXPERIMENTAL
DATA
.
78
5.3.2
RESULTS
FROM
PREVIOUS
WORK
.
78
5.3.3
BOXPLOTS
.
78
5.3.4
ERROR
DISTRIBUTION
.
79
5.3.5
TAGGING
ERROR
DENSITY
.
81
5.3.6
NORMAL
PROBABILITY
PLOT
.
82
5.3.7
THE
ROLE
OF
CONTEXTUAL
PROBABILITIES
.
83
5.3.8
BIGRAMS
VERSUS
TRIGRAMS
.
84
5.3.9
THE
IMPORTANCE
OF
SMOOTHING
TRIGRAMS
.
85
5.3.10
LEXICAL
PROBABILITIES
AND
UNKNOWN
WORDS
.
85
5.3.11
POS
TAGGING
AND
UNKNOWN
WORDS
.
87
5.3.12
UNKNOWN
WORD
MODEL
RESULTS
.
88
5.3.13
EFFECT
OF
STATISTICAL
MODEL
ON
NEW
TEXT
.
88
5.4
ERRORS
ANALYSIS
FOR
THE
TRIGRAM-BASED
TAGGER
.
89
5.4.1
QUALITATIVE
ERROR
ANALYSIS
.
90
5.4.2
QUANTITATIVE
ERROR
ANALYSIS
.
91
5.4.3
OVERALL
ERROR
DISTRIBUTION
OF
THE
STOCHASTIC
TAGGER
.
91
5.4.4
CONFUSION
MATRIX
OF
THE
STOCHASTIC
TAGGER
.
91
5.4.5
RESULTS
OF
ERROR
ANALYSIS
.
92
5.5
USING
A
LOGLINEAR
MODEL
FOR
LEXICAL
DISAMBIGUATION
.
93
5.5.1
ERRORS
BEFORE
CORRECTION
.
93
5.5.2
FEATURES
FOR
TAGGING
CORRECTION
.
94
5.5.3
RESULTS
OF
TAGGING
CORRECTION
.
95
5.5.4
SUMMARY
OF
RESULTS
.
95
XIV
TABLE
OF
CONTENTS
6.
PREPOSITIONAL
PHRASE
ATTACHMENT
DISAMBIGUATION
.
97
6.1
OVERVIEW
OF
PP
EXPERIMENTS
.
97
6.2
FEATURES
FOR
PP
ATTACHMENT
.
97
6.3
EXPERIMENTAL
DATA
AND
EVALUATION
.
99
6.4
EXPERIMENTAL
RESULTS:
TWO
ATTACHMENTS
SITES
.
100
6.4.1
BASELINE:
RIGHT
ASSOCIATION
.
100
6.4.2
RESULTS
OF
LEXICAL
ASSOCIATION
.
101
6.4.3
RESULTS
OF
THE
LOGLINEAR
MODEL
.
102
6.5
EXPERIMENTAL
RESULTS:
THREE
ATTACHMENT
SITES
.
J
.
102
6.5.1
ADDITIONAL
PP
PATTERNS
.
102
6.5.2
BASELINE:
RIGHT
ASSOCIATION
.
103
6.5.3
RESULTS
OF
LEXICAL
ASSOCIATION
.
103
6.5.4
RESULTS
OF
ENHANCED
LEXICAL
ASSOCIATION
.
104
6.5.5
RESULTS
OF
THE
LOGLINEAR
MODEL
.
104
6.5.6
ANALYSIS
OF
RESULTS
.
105
6.6
HUMAN
PERFORMANCE
ON
PP
ATTACHMENT
.
107
6.7
DISCUSSION
OF
PP
EXPERIMENTS
.
107
7.
CONCLUSIONS
.
109
7.1
SUMMARY
OF
THIS
WORK
.
109
7.1.1
MODELING
UNKNOWN
WORDS
.
109
7.1.2
PART-OF-SPEECH
DISAMBIGUATION
.
109
7.1.3
PREPOSITIONAL
PHRASE
ATTACHMENT
DISAMBIGUATION
.
110
7.2
CONTRIBUTIONS
OF
THIS
WORK
.
110
7.2.1
AUTOMATIC
NATURAL
LANGUAGE
AMBIGUITY
RESOLUTION
.
110
7.2.2
STATISTICAL
LANGUAGE
MODELING
.
ILL
7.2.3
TOWARDS
A
THEORY
OF
AMBIGUITY
.
ILL
7.3
FUTURE
WORK
.
112
7.3.1
IMPROVING
THE
MODELS
.
113
7.3.2
APPLICATION
TO
OTHER
AMBIGUITY
PROBLEMS
.
113
7.3.3
INTEGRATION
WITH
OTHER
KNOWLEDGE
SOURCES
.
114
7.3.4
COSTS
AND
BENEFITS
OF
LOGLINEAR
AMBIGUITY
RESOLUTION
MODELS
.
115
7.4
TOWARDS
A
UNIFIED
MODEL
.
115
A.
ENTROPY
.
117
B.
PENN
TREEBANK
TAGS
.
119
C.
OBTAINING
RANDOM
SAMPLES
.
121
D.
CONFUSION
MATRICES
FOR
POS
TAGGING
.
123
E.
CONVERTING
TREEBANK
FILES
.
125
F.
INPUT
TO
AND
OUTPUT
FROM
THE
ESTIMATION
ROUTINES
.
129
TABLE
OF
CONTENTS
XV
REFERENCES
.
133
INDEX
.
147 |
| any_adam_object | 1 |
| author | Franz, Alexander |
| author_facet | Franz, Alexander |
| author_role | aut |
| author_sort | Franz, Alexander |
| author_variant | a f af |
| building | Verbundindex |
| bvnumber | BV011034940 |
| callnumber-first | Q - Science |
| callnumber-label | QA76 |
| callnumber-raw | QA76.9.N38F75 1996 |
| callnumber-search | QA76.9.N38F75 1996 |
| callnumber-sort | QA 276.9 N38 F75 41996 |
| callnumber-subject | QA - Mathematics |
| classification_rvk | SS 4800 |
| classification_tum | DAT 710f |
| ctrlnum | (OCoLC)845312580 (DE-599)BVBBV011034940 |
| dewey-full | 006.35 006.3/521 |
| dewey-hundreds | 000 - Computer science, information, general works |
| dewey-ones | 006 - Special computer methods |
| dewey-raw | 006.35 006.3/5 21 |
| dewey-search | 006.35 006.3/5 21 |
| dewey-sort | 16.35 |
| dewey-tens | 000 - Computer science, information, general works |
| discipline | Informatik |
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| id | DE-604.BV011034940 |
| illustrated | Illustrated |
| indexdate | 2024-08-19T00:28:30Z |
| institution | BVB |
| isbn | 3540620044 |
| language | English |
| oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-007389621 |
| oclc_num | 845312580 |
| open_access_boolean | |
| owner | DE-384 DE-739 DE-91G DE-BY-TUM DE-29T DE-20 DE-19 DE-BY-UBM DE-706 DE-634 DE-83 |
| owner_facet | DE-384 DE-739 DE-91G DE-BY-TUM DE-29T DE-20 DE-19 DE-BY-UBM DE-706 DE-634 DE-83 |
| physical | XV, 155 S. graph. Darst. |
| publishDate | 1996 |
| publishDateSearch | 1996 |
| publishDateSort | 1996 |
| publisher | Springer |
| record_format | marc |
| series | Lecture notes in computer science |
| series2 | Lecture notes in computer science |
| spelling | Franz, Alexander Verfasser aut Automatic ambiguity resolution in natural language processing an empirical approach Alexander Franz Berlin u.a. Springer 1996 XV, 155 S. graph. Darst. txt rdacontent n rdamedia nc rdacarrier Lecture notes in computer science 1171 : Lecture notes in artificial intelligence Natural language processing (Computer science) Ambiguity Natürlichsprachiges System (DE-588)4284757-6 gnd rswk-swf Natürliche Sprache (DE-588)4041354-8 gnd rswk-swf Syntaktische Analyse (DE-588)4058778-2 gnd rswk-swf Ambiguität (DE-588)4138525-1 gnd rswk-swf Sprachverarbeitung (DE-588)4116579-2 gnd rswk-swf Ambiguität (DE-588)4138525-1 s Natürlichsprachiges System (DE-588)4284757-6 s DE-604 Natürliche Sprache (DE-588)4041354-8 s Sprachverarbeitung (DE-588)4116579-2 s Syntaktische Analyse (DE-588)4058778-2 s Lecture notes in computer science 1171 : Lecture notes in artificial intelligence (DE-604)BV000000607 1171 DNB Datenaustausch application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=007389621&sequence=000001&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA Inhaltsverzeichnis |
| spellingShingle | Franz, Alexander Automatic ambiguity resolution in natural language processing an empirical approach Lecture notes in computer science Natural language processing (Computer science) Ambiguity Natürlichsprachiges System (DE-588)4284757-6 gnd Natürliche Sprache (DE-588)4041354-8 gnd Syntaktische Analyse (DE-588)4058778-2 gnd Ambiguität (DE-588)4138525-1 gnd Sprachverarbeitung (DE-588)4116579-2 gnd |
| subject_GND | (DE-588)4284757-6 (DE-588)4041354-8 (DE-588)4058778-2 (DE-588)4138525-1 (DE-588)4116579-2 |
| title | Automatic ambiguity resolution in natural language processing an empirical approach |
| title_auth | Automatic ambiguity resolution in natural language processing an empirical approach |
| title_exact_search | Automatic ambiguity resolution in natural language processing an empirical approach |
| title_full | Automatic ambiguity resolution in natural language processing an empirical approach Alexander Franz |
| title_fullStr | Automatic ambiguity resolution in natural language processing an empirical approach Alexander Franz |
| title_full_unstemmed | Automatic ambiguity resolution in natural language processing an empirical approach Alexander Franz |
| title_short | Automatic ambiguity resolution in natural language processing |
| title_sort | automatic ambiguity resolution in natural language processing an empirical approach |
| title_sub | an empirical approach |
| topic | Natural language processing (Computer science) Ambiguity Natürlichsprachiges System (DE-588)4284757-6 gnd Natürliche Sprache (DE-588)4041354-8 gnd Syntaktische Analyse (DE-588)4058778-2 gnd Ambiguität (DE-588)4138525-1 gnd Sprachverarbeitung (DE-588)4116579-2 gnd |
| topic_facet | Natural language processing (Computer science) Ambiguity Natürlichsprachiges System Natürliche Sprache Syntaktische Analyse Ambiguität Sprachverarbeitung |
| url | http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=007389621&sequence=000001&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA |
| volume_link | (DE-604)BV000000607 |
| work_keys_str_mv | AT franzalexander automaticambiguityresolutioninnaturallanguageprocessinganempiricalapproach |