The document discusses the Pullenti NER Engine and its use in semantic similarity tasks. It presents the Semantics-Oriented Linguistic Processor (SOLP) which establishes text segments containing similar semantic units. It then describes the hybrid linguistic and machine learning approach used by the Pullenti-based engine, including the two-step Semantic Expansion Algorithm. Performance figures and evaluation metrics for Pullenti's named entity recognition are also provided.

1. The Pullenti NER Engine in the
Tasks of Semantic Similarity
Establishment
Kuznetsov K.I. (k.smith@mail.ru),
Kozerenko E.B. (kozerenko@mail.ru),
Romanov D.A. DRomanov@it.ru
FRC “Computer Science and Control”
NRU HSE
AINL FRUCT 2016
суббота, 12 ноября 16 г.

2. Semantics-Oriented Linguistic
Processor (SOLP)
• Establishing text segments containing
the similar semantic units for the tasks
of analytical text processing within the
semantic technology platform.
• The methods and instruments
presented provide the discovery of
relevant content based on users'
focused interests within a certain
domain.
2
суббота, 12 ноября 16 г.

3. Basic Ideas
• The hybrid approach comprising
linguistic rules and example-based
learning techniques is employed.
• The Pullenti-based engine is specified,
the two-step Semantic Expansion
Algorithm is presented.
• The legal and mass media texts are
considered. 3
суббота, 12 ноября 16 г.

4. Pullenti Engine Features
• Pullenti is used as the engine for
selecting entities and structuring
information.
• The feature set comprises common
morphological algorithms and parsing.
Modules are focused on the
identification of specific entities.
суббота, 12 ноября 16 г.

5. Linguistic Processing
• The system integrates the seed feature-
value unification grammar which is
extensible by creating new rule-based
modules and incremental machine-
learning components extracting phrase
structures from texts under study.
суббота, 12 ноября 16 г.

6. Pullenti Implementation
• The system is implemented as a
software development kit (SDK) for
information systems development
dealing with unstructured data, i.e.
texts in natural languages, for use in
the systems developed in .NET
environment. For Mac and Linux
systems it is running on Mono
platform.
суббота, 12 ноября 16 г.

7. Software Development Kit
• The SDK is completely written in C #
and .NET, it is a set of assemblies
of .NET Framework (2.0 and above).
Third-party extensions are not used.
• If necessary, one can take the form of a
standard service for unstructured
information processing UIMA
(Unstructured Information
Management Architecture).
суббота, 12 ноября 16 г.

8. Semantics Expansion
Algorithm
• The two steps of the Semantics Expansion
Algorithm (SEA):
• a text of a newly received application to
the Constitutional Court (CC) is matched
to a list of links to the profile of the
applications traced by links to Normative
Legal Acts (NLA) and legal norms (LN)
(meaningful terms and bigrams).
суббота, 12 ноября 16 г.

9. The Pullenti-based technology
• The Pullenti-based technology is a
novel development designed from
scratch four years ago:
• http://semantick.ru/
• http://pullenti.ru/DemoPage.aspx
• http://semantick.ru/Ner.aspx
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10. Performance
• The work speed can be very
approximately estimated as
60.000-80.000 characters per second
on a serial computer model. The
maximum amount of text on a 32-bit
computer that can be processed at one
time is no more than 20 MB. On a 64-
bit processor the result depends on the
size of the operational memory.
суббота, 12 ноября 16 г.

11. Evaluation
• The Precision (P), Recall (R) and F-
measure demonstrated by Pullenti for
the NER tasks are as follows:
• P = 0.7957-0.9663;
• R = 0.7091-0.8675;
• F-measure = 0.8083-0.8570.
•
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12. Competition Results
• The Pullenti-based engine participated
in the NER competition organized for
the Dialog 2016 Conference
(nickname Pink):
• http://www.dialog-21.ru/media/3430/
starostinaetal.pdf
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13. Terms of Use
• The system is free for non-commercial
use and it can be downloaded. For
commercial use the SDK is shipped
without restrictions on the number of
end users and installations:
http://semantick.ru/Technology.aspx
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14. AINL Prototyping Environment
•www.ipiranlogos.com
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15. • Thank you!
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