Volume 03 Issue 08-2023
6
American Journal Of Philological Sciences
(ISSN
–
2771-2273)
VOLUME
03
ISSUE
08
P
AGES
:
6-10
SJIF
I
MPACT
FACTOR
(2022:
5.
445
)
(2023:
6.
555
)
OCLC
–
1121105677
Publisher:
Oscar Publishing Services
Servi
ABSTRACT
FrameNet is a valuable lexical resource that captures the meaning and structure of words in terms of frames and their
associated lexical units. However, its applicability to diverse natural languages is often hindered by language-specific
variations in thematic role structures. This research proposes a novel approach to link FrameNet with multiple natural
languages by establishing universal thematic role structures. By aligning thematic roles across languages, this study
aims to enhance linguistic analysis and facilitate cross-lingual information retrieval, machine translation, and sentiment
analysis. The proposed method leverages linguistic typology and cross-lingual learning techniques to create a unified
framework for integrating FrameNet with various languages, promoting a deeper understanding of lexical semantics
and facilitating language technology applications.
KEYWORDS
Thematic role structures, FrameNet, natural languages, linguistic typology, cross-lingual learning, lexical semantics,
linguistic analysis, cross-lingual information retrieval, machine translation, sentiment analysis, lexical units, frames,
language technology applications.
INTRODUCTION
Research Article
THE MATIC ROLE STRUCTURES: BRIDGING FRAMENET AND NATURAL
LANGUAGES FOR ENHANCED LINGUISTIC ANALYSIS
Submission Date:
July 28, 2023,
Accepted Date:
Aug 02, 2023,
Published Date:
Aug 07, 2023
Crossref doi:
https://doi.org/10.37547/ajps/Volume03Issue08-02
Yılmaz Tuna
Associate Professor at The Department of Computer Programming of Trakya University, Turkey
Journal
Website:
https://theusajournals.
com/index.php/ajps
Copyright:
Original
content from this work
may be used under the
terms of the creative
commons
attributes
4.0 licence.
Volume 03 Issue 08-2023
7
American Journal Of Philological Sciences
(ISSN
–
2771-2273)
VOLUME
03
ISSUE
08
P
AGES
:
6-10
SJIF
I
MPACT
FACTOR
(2022:
5.
445
)
(2023:
6.
555
)
OCLC
–
1121105677
Publisher:
Oscar Publishing Services
Servi
FrameNet is a valuable linguistic resource that provides
a comprehensive and systematic representation of
lexical semantics. It organizes words into frames,
which are abstract structures capturing the meaning
and typical situations associated with a word or
concept. Each frame is linked to specific lexical units
representing the word's different senses or usages.
FrameNet has been extensively developed for English,
offering in-depth insights into the semantics of words
in this language. However, its application to other
natural languages is challenging due to language-
specific variations in thematic role structures.
Thematic roles are essential for understanding how
different elements in a sentence relate to each other
and play specific semantic roles. In FrameNet, these
thematic roles are associated with individual lexical
units and frames, providing rich information about the
syntactic and semantic behavior of words in a given
context. However, when extending FrameNet to other
languages, these thematic roles often exhibit
variations, making it difficult to establish direct
connections between the English-based FrameNet and
other languages.
This research proposes a novel approach to bridge the
gap between FrameNet and multiple natural languages
by creating universal thematic role structures. By
aligning thematic roles across languages, this study
aims to enable a deeper understanding of lexical
semantics and enhance linguistic analysis in
multilingual settings. The establishment of universal
thematic role structures will facilitate cross-lingual
information retrieval, machine translation, sentiment
analysis, and other language technology applications.
METHOD
FrameNet Data Compilation:
A comprehensive FrameNet dataset for English is
compiled, encompassing a diverse set of frames and
their associated lexical units. Each lexical unit is
annotated with its corresponding thematic roles.
Linguistic Typology Analysis:
Linguistic typology principles are employed to identify
commonalities and differences in thematic role
structures across languages. Linguistic typology helps
identify recurring patterns and generalizations that can
serve as a basis for creating universal thematic roles.
Thematic Role Alignment:
Based on linguistic typology analysis, an algorithm is
developed to align thematic roles from FrameNet with
their counterparts in other languages. The algorithm
seeks to establish correspondences between similar
roles and accommodate language-specific variations.
Cross-Lingual Learning:
Machine learning techniques, including cross-lingual
learning, are applied to fine-tune the thematic role
Volume 03 Issue 08-2023
8
American Journal Of Philological Sciences
(ISSN
–
2771-2273)
VOLUME
03
ISSUE
08
P
AGES
:
6-10
SJIF
I
MPACT
FACTOR
(2022:
5.
445
)
(2023:
6.
555
)
OCLC
–
1121105677
Publisher:
Oscar Publishing Services
Servi
alignment algorithm. This process involves training on
bilingual data to improve the accuracy of cross-lingual
alignment.
Evaluation:
The proposed approach is evaluated on multiple
natural languages, including typologically diverse
languages, to assess its effectiveness in linking
FrameNet with different linguistic contexts. Evaluation
metrics, such as precision, recall, and F1 score, are used
to measure the alignment accuracy.
Application to Language Technology:
The utility of the established universal thematic role
structures is demonstrated through their application in
various language technology tasks, such as cross-
lingual information retrieval, machine translation, and
sentiment analysis. The performance of these tasks is
compared with and without the use of the aligned
thematic roles.
The proposed approach aims to contribute to the
advancement of linguistic analysis and language
technology applications in multilingual environments.
By bridging FrameNet with natural languages via
universal thematic role structures, this research
facilitates a deeper understanding of lexical semantics
and promotes more effective cross-lingual information
processing and communication.
RESULTS
The proposed approach for bridging FrameNet and
natural languages through universal thematic role
structures demonstrated promising results. Thematic
role alignment across multiple languages using
linguistic
typology
and
cross-lingual
learning
techniques achieved a high level of accuracy. The
establishment of universal thematic role structures
enabled a more effective understanding of lexical
semantics and facilitated enhanced linguistic analysis
in multilingual settings.
DISCUSSION
The successful alignment of thematic roles between
FrameNet and diverse natural languages opens up new
possibilities for cross-lingual information processing
and language technology applications. By creating a
unified framework for representing thematic roles, the
proposed approach overcomes language-specific
variations and enables seamless integration of
FrameNet with multiple languages.
The application of the established universal thematic
role structures in language technology tasks
showcased significant improvements. Cross-lingual
information retrieval benefited from the enhanced
understanding of word semantics across languages,
leading to more relevant search results. Machine
translation systems, equipped with the aligned
thematic roles, demonstrated improved translation
Volume 03 Issue 08-2023
9
American Journal Of Philological Sciences
(ISSN
–
2771-2273)
VOLUME
03
ISSUE
08
P
AGES
:
6-10
SJIF
I
MPACT
FACTOR
(2022:
5.
445
)
(2023:
6.
555
)
OCLC
–
1121105677
Publisher:
Oscar Publishing Services
Servi
accuracy and naturalness, as they better captured the
semantic nuances of source sentences. Sentiment
analysis in multilingual contexts also achieved better
performance by leveraging the universal thematic role
structures to extract more accurate sentiment-bearing
elements from texts.
The alignment of thematic roles using linguistic
typology and cross-lingual learning techniques proved
to be robust across different language families and
typologically diverse languages. This universality of the
approach highlights its potential to be applied to
various linguistic contexts, making it a valuable
resource for researchers and developers working on
multilingual natural language processing tasks.
CONCLUSION
The research presents a successful approach for
bridging FrameNet and natural languages through the
establishment of universal thematic role structures. By
aligning thematic roles across languages, this approach
enables a deeper understanding of lexical semantics
and enhances linguistic analysis in multilingual settings.
The results of the evaluation and application of the
aligned thematic roles in language technology tasks
demonstrate the effectiveness and practical utility of
the proposed approach. The aligned thematic roles
contribute to more accurate and contextually relevant
information retrieval, translation, and sentiment
analysis in multilingual environments.
Overall, the research advances the field of cross-lingual
natural language processing and contributes to the
development of language technology tools that can
effectively
handle
linguistic
diversity.
The
establishment of universal thematic role structures
offers
a
valuable
resource
for
researchers,
practitioners, and developers seeking to bridge the
gap between lexical semantics and linguistic analysis in
different natural languages. By facilitating enhanced
cross-lingual understanding and communication, the
proposed approach has the potential to significantly
impact various language-related applications and
contribute to the advancement of multilingual
language technology.
REFERENCES
1.
C. J. Fillmore, “Frame semantics and the nature of
language,” in Origins and Evolution of Language
and Speech, vol. 280, S. R. Harnad, H. D. Steklis, and
J. Lancaster, Eds. 1976, pp. 20-32.
2.
C. J. Fillmore, “The need for frame semantics within
linguistics,”
Statistical Methods in Linguistics, vol.
12, pp. 5-29, 1976.
3.
C. J. Fillmore, “Scenes
-and-
frames semantics,” in
Linguistics Structures Processing, A. Zampolli, Ed.
Amsterdam and New York: North Holland
Publishing Company, 1977, pp. 55-81.
4.
C. J. Fillmore, “Frame semantics,” in Linguistics in
the Morning Calm, D. Geeraerts Ed. Seoul: Hanshin
Publishing, 1982, pp. 111-137.
Volume 03 Issue 08-2023
10
American Journal Of Philological Sciences
(ISSN
–
2771-2273)
VOLUME
03
ISSUE
08
P
AGES
:
6-10
SJIF
I
MPACT
FACTOR
(2022:
5.
445
)
(2023:
6.
555
)
OCLC
–
1121105677
Publisher:
Oscar Publishing Services
Servi
5.
C. J. Fillmore, “Frames and the semantics of
understanding,” Quaderni di Semantica, vol. 6, no.
2, pp. 222-254, 1985.
6.
C. J. Fillmore and B.
T. S. Atkins, “Toward a frame
-
based lexicon: The semantics of RISK and its
neighbors,” in Frames, Fields, and Contrasts, A.
Lehrer and E. F. Kittay, Eds. NJ: Lawrence Erlbaum
Associates Hillsdale, 1992, pp. 74
–
102.
7.
C. J. Fillmore and B. T. S. Atkins, “Fra
meNet and
lexicographic relevance,” in Proc. LREC, Granada,
Spain, 1998.
8.
C. J. Fillmore and C. F. Baker, “Frame semantics for
text understanding,” in Proc. WordNet and Other
Lexical Resources Workshop, 2001.
9.
C. J. Fillmore and C. F. Baker, “A frames approa
ch
to semantic analysis,” in the Oxford Handbook of
Linguistic Analysis, B. Heine and H. Narrog, Eds.
Oxford: Oxford University Press, 2010, pp. 313-340.
10.
C. J. Fillmore, C. R. Johnson, and M. R. L. Petruck,
“Background to FrameNet,” International Journal
of Lexicography, vol. 16, no. 3, pp. 235-250, 2003.
