Manufacturing companies maintain manufacturing knowledge primarily as unstructured text. To facilitate formal use of such knowledge, previous efforts have utilized natural language processing (NLP) to classify manufacturing documents or extract manufacturing concepts/relations. However, extracting more complex knowledge, such as manufacturing rules, has been evasive due to the lack of methods to resolve ambiguities. Specifically, standard NLP techniques do not address domain-specific ambiguities that are due to manufacturing-specific meanings implicit in the text. To address this important gap, we propose an ambiguity resolution method that utilizes domain ontology as the mechanism to incorporate the domain context. We demonstrate its feasibility by extending our previously implemented manufacturing rule extraction framework. The effectiveness of the method is demonstrated by resolving all the domain-specific ambiguities in the dataset and an improvement in correct detection of rules to 70% (increased by about 13%). We expect that this work will contribute to the adoption of semantics-based technology in manufacturing field, by enabling the extraction of precise formal knowledge from text.

References

References
1.
Ur-Rahman
,
N.
, and
Harding
,
J. A.
,
2012
, “
Textual Data Mining for Industrial Knowledge Management and Text Classification: A Business Oriented Approach
,”
Expert Syst. Appl.
,
39
(
5
), pp.
4729
4739
.
2.
Boonyasopon
,
P.
,
Riel
,
A.
,
Uys
,
W.
,
Louw
,
L.
,
Tichkiewitch
,
S.
, and
du Preez
,
N.
,
2011
, “
Automatic Knowledge Extraction From Manufacturing Research Publications
,”
CIRP Ann.-Manuf. Technol.
,
60
(
1
), pp.
477
480
.
3.
Shotorbani
,
P. Y.
,
Ameri
,
F.
,
Kulvatunyou
,
B.
, and
Ivezic
,
N.
,
2016
, “
A Hybrid Method for Manufacturing Text Mining Based on Document Clustering and Topic Modeling Techniques
,”
IFIP
International Conference on Advances in Production Management Systems
, Iguassu Falls, Brazil, Sept. 3–7, pp.
777
786
.https://ws680.nist.gov/publication/get_pdf.cfm?pub_id=920918
4.
Li
,
Z.
, and
Ramani
,
K.
,
2007
, “
Ontology-Based Design Information Extraction and Retrieval
,”
Artif. Intell. Eng. Des. Anal. Manuf.
,
21
(
2
), pp.
137
154
.
5.
Cheong
,
H.
,
Li
,
W.
, and
Iorio
,
F.
,
2016
, “
Automated Extraction of System Structure Knowledge From Text
,”
ASME
Paper No. DETC2016-59551.
6.
Wang
,
G.
,
Tian
,
X.
,
Geng
,
J.
,
Evans
,
R.
, and
Che
,
S.
,
2016
, “
Extraction of Principle Knowledge From Process Patents for Manufacturing Process Innovation
,”
Procedia CIRP
,
56
, pp.
193
198
.
7.
Li
,
Z.
,
Yang
,
M. C.
, and
Ramani
,
K.
,
2009
, “
A Methodology for Engineering Ontology Acquisition and Validation
,”
Artif. Intell. Eng. Des. Anal. Manuf.
,
23
(
1
), pp.
37
51
.
8.
Ameri
,
F.
,
Kulvatunyou
,
B.
,
Ivezic
,
N.
, and
Kaikhah
,
K.
,
2014
, “
Ontological Conceptualization Based on the SKOS
,”
ASME J. Comput. Inf. Sci. Eng.
,
14
(
3
), p.
031006
.
9.
Rangarajan
,
A.
,
Radhakrishnan
,
P.
,
Moitra
,
A.
,
Crapo
,
A.
, and
Robinson
,
D.
,
2013
, “
Manufacturability Analysis and Design Feedback System Developed Using Semantic Framework
,”
ASME
Paper No. DETC2013-12028.
10.
Kang
,
S.
,
Patil
,
L.
,
Rangarajan
,
A.
,
Moitra
,
A.
,
Jia
,
T.
,
Robinson
,
D.
, and
Dutta
,
D.
,
2015
, “
Extraction of Manufacturing Rules From Unstructured Text Using a Semantic Framework
,”
ASME
Paper No. DETC2015-47556.
11.
Franz
,
A.
,
1996
,
Automatic Ambiguity Resolution in Natural Language Processing: An Empirical Approach
, Vol.
1171
, Springer, Berlin.
12.
Poesio
,
M.
,
Stuckardt
,
R.
, and
Versley
,
Y.
,
2016
,
Anaphora Resolution: Algorithms, Resources, and Applications
,
Springer
, Berlin.
13.
Lappin
,
S.
, and
Leass
,
H. J.
,
1994
, “
An Algorithm for Pronominal Anaphora Resolution
,”
Comput. Linguist.
,
20
(
4
), pp.
535
561
.
14.
Mitkov
,
R.
,
1994
, “
An Integrated Model for Anaphora Resolution
,”
15th Conference on Computational Linguistics
, Kyoto, Japan, Aug. 5–9, pp.
1170
1176
.
15.
Mitkov
,
R.
,
1998
, “
Robust Pronoun Resolution With Limited Knowledge
,”
36th Annual Meeting of the Association for Computational Linguistics and 17th International Conference on Computational Linguistics
, Montreal, QC, Canada, Aug. 10–14, pp.
869
875
.
16.
Dagan
,
I.
, and
Itai
,
A.
,
1990
, “
Automatic Processing of Large Corpora for the Resolution of Anaphora References
,”
13th Conference on Computational Linguistics
, Helsinki, Finland, Aug. 20–25, pp.
330
332
.
17.
Iida
,
R.
,
Inui
,
K.
, and
Matsumoto
,
Y.
,
2005
, “
Anaphora Resolution by Antecedent Identification Followed by Anaphoricity Determination
,”
ACM Trans. Asian Lang. Inf. Process.
,
4
(
4
), pp.
417
434
.
18.
Lee
,
H.
,
Chang
,
A.
,
Peirsman
,
Y.
,
Chambers
,
N.
,
Surdeanu
,
M.
, and
Jurafsky
,
D.
,
2013
, “
Deterministic Coreference Resolution Based on Entity-Centric, Precision-Ranked Rules
,”
Comput. Linguist.
,
39
(
4
), pp.
885
916
.
19.
Ponzetto
,
S. P.
, and
Strube
,
M.
,
2006
, “
Exploiting Semantic Role Labeling, Wordnet and Wikipedia for Coreference Resolution
,”
Main Conference on Human Language Technology Conference of the North American Chapter of the Association of Computational Linguistics
, New York, June 4–9, pp.
192
199
.
20.
Miller
,
G. A.
,
1995
, “
WordNet: A Lexical Database for English
,”
Commun. ACM
,
38
(
11
), pp.
39
41
.
21.
Bryl
,
V.
,
Giuliano
,
C.
,
Serafini
,
L.
, and
Tymoshenko
,
K.
,
2010
, “
Supporting Natural Language Processing With Background Knowledge: Coreference Resolution Case
,” International Semantic Web Conference (
ISWC
), Shanghai, China, Nov. 7–11, pp.
80
95
.
22.
Auer
,
S.
,
Bizer
,
C.
,
Kobilarov
,
G.
,
Lehmann
,
J.
,
Cyganiak
,
R.
, and
Ives
,
Z.
,
2007
, “
DBpedia: A Nucleus for a Web of Open Data
,”
The Semantic Web
,
Springer
,
Berlin
, pp.
722
735
.
23.
Suchanek
,
F. M.
,
Kasneci
,
G.
, and
Weikum
,
G.
,
2007
, “
YAGO: A Core of Semantic Knowledge
,”
16th International Conference on World Wide Web
, Banff, AB, Canada, May 8–12, pp.
697
706
.
24.
Uryupina
,
O.
,
Poesio
,
M.
,
Giuliano
,
C.
, and
Tymoshenko
,
K.
,
2011
, “
Disambiguation and Filtering Methods in Using Web Knowledge for Coreference Resolution
,”
FLAIRS Conference
, Palm Beach, FL, May 18--20, pp.
317
322
.
25.
Resnik
,
P.
,
1999
, “
Semantic Similarity in a Taxonomy: An Information-Based Measure and Its Application to Problems of Ambiguity in Natural Language
,”
J. Artif. Intell. Res.
,
11
, pp.
95
130
.
26.
Nakov
,
P.
, and
Hearst
,
M.
,
2005
, “
Using the Web as an Implicit Training Set: Application to Structural Ambiguity Resolution
,”
Conference on Human Language Technology and Empirical Methods in Natural Language Processing
, Vancouver, BC, Canada, Oct. 6–8, pp.
835
842
.
27.
Ogren
,
P. V.
,
2010
, “
Improving Syntactic Coordination Resolution Using Language Modeling
,”
Human Language Technologies: The 2010 Annual Conference of the North American Chapter of the Association for Computational Linguistics: Student Research Workshop
, Los Angeles, CA, June 1–6, pp.
1
6
.
28.
Hanamoto
,
A.
,
Matsuzaki
,
T.
, and
Tsujii
,
J.
,
2012
, “
Coordination Structure Analysis Using Dual Decomposition
,”
13th Conference of the European Chapter of the Association for Computational Linguistics
, Avignon, France, Apr. 23–27, pp.
430
438
.
29.
Nilsson
,
J.
,
Nivre
,
J.
, and
Hall
,
J.
,
2006
, “
Graph Transformations in Data-Driven Dependency Parsing
,”
21st International Conference on Computational Linguistics and the 44th Annual Meeting of the Association for Computational Linguistics
, Sydney, Australia, July 20, pp.
257
264
.
30.
Hogan
,
D.
,
2007
, “
Coordinate Noun Phrase Disambiguation in a Generative Parsing Model
,”
45th Annual Meeting of the Association of Computational Linguistics
, Prague, Czech Republic, June 23–30, pp.
680
687
.
31.
Choi, D. J.
, “
The Natural Language Processing for JVM Languages (NLP4J)
,” JVM Languages, Santa Clara, CA, accessed Oct. 12, 2018, https://emorynlp.github.io/nlp4j/
32.
Bralla
,
J.
,
1998
,
Design for Manufacturability Handbook
,
McGraw-Hill Professional
, New York.
33.
Ameri
,
F.
, and
Dutta
,
D.
,
2006
, “
An Upper Ontology for Manufacturing Service Description
,”
ASME
Paper No. DETC2006-99600.
34.
Crapo
,
A.
, and
Moitra
,
A.
,
2013
, “
Toward a Unified English-Like Representation of Semantic Models, Data, and Graph Patterns for Subject Matter Experts
,”
Int. J. Semantic Comput.
,
7
(
3
), pp.
215
236
.
35.
Kottmann
,
J.
,
Ingersoll
,
G.
,
Drost
,
I.
,
Kosin
,
J.
,
Baldridge
,
J.
,
Morton
,
T.
,
Silva
,
W.
,
Agerri
,
R.
,
Autayeu
,
A.
,
Galitsky
,
B.
,
Giaconia
,
M.
,
Teofili
,
T.
,
Khuc
,
V.
,
Beylerian
,
A.
,
Bouazizi
,
M.
,
Mattmann
,
C.
,
Mensikova
,
A.
,
Marthi
,
S.
,
Russ
,
D.
,
Thygesen
,
P.
,
Sekiguchi
,
K.
,
Kinoshita
,
P. B.
, and
Zemerick
,
J.
, 2018, “
Apache OpenNLP
,” Apache Software Foundation, Forest Hill, MD, accessed Oct. 12, 2018, https://opennlp.apache.org/
36.
Seaborne
,
A.
,
Soroka
,
A.
,
Kinoshita
,
B.
,
Dollin
,
C.
,
Tomlinson
,
C.
,
Warren
,
C.
,
Steer
,
D.
,
Reynolds
,
D.
,
Dickinson
,
I.
,
Buehmann
,
L.
,
Suominen
,
O.
,
Castagna
,
P.
,
Vesse
,
R.
,
Allen
,
S.
, and
Jiang
,
Y.
, 2018, “
Apache Jena
,” Apache Software Foundation, Forest Hill, MD, accessed Oct.12, 2018, https://jena.apache.org/
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