Subject
Programming Techniques for NLP
General details of the subject
- Mode
- Face-to-face degree course
- Language
- English
Description and contextualization of the subject
El objetivo del curso es que los estudiantes usen con un enfoque totalmente práctico basado en ejercicios, herramientas de software utilizadas en el procesamiento del lenguaje natural (PLN). Durante el curso se verá una breve introducción al lenguaje de programación Python, incluyendo paquetes específicos para el PLN y ejercicios con el estándares para representar información lingüística en textos.Teaching staff
Name | Institution | Category | Doctor | Teaching profile | Area | |
---|---|---|---|---|---|---|
PEREZ DE VIÑASPRE GARRALDA, OLATZ | University of the Basque Country | Profesorado Adjunto (Ayudante Doctor/A) | Doctor | Bilingual | Computer Architecture and Technology | olatz.perezdevinaspre@ehu.eus |
SARASOLA GABIOLA, KEPA MIRENA | University of the Basque Country | Profesorado Pleno | Doctor | Bilingual | Computer Languages and Systems | kepa.sarasola@ehu.eus |
Competencies
Name | Weight |
---|---|
Ability to manage and design systems based on standard languages for the labelling of linguistic information. | 25.0 % |
Ability to manage, enrich and manage linguistic resources for human language processing. | 25.0 % |
Ability to manage knowledge-based strategies and tools for human language processing. | 25.0 % |
Ability to use and adapt the most relevant symbolic and corpus-based methods (automatic learning) for research into language technologies. | 25.0 % |
Study types
Type | Face-to-face hours | Non face-to-face hours | Total hours |
---|---|---|---|
Lecture-based | 20 | 30 | 50 |
Applied laboratory-based groups | 40 | 60 | 100 |
Training activities
Name | Hours | Percentage of classroom teaching |
---|---|---|
Computer work practice, laboratory, site visits, field trips, external visits | 100.0 | 40 % |
Lectures | 50.0 | 40 % |
Assessment systems
Name | Minimum weighting | Maximum weighting |
---|---|---|
OTROS | 20.0 % | 20.0 % |
Practical tasks | 40.0 % | 40.0 % |
Presentations | 20.0 % | 20.0 % |
Written examination | 20.0 % | 20.0 % |
Learning outcomes of the subject
Work with basic problems that require treatment of sequences, lists, plain text ¿Know the basic elements of structured and modular programming: (a) control structures: sequential, conditional and iterative, (b) subprograms and (c) data structures.
Learn to write code and use relevant Python libraries or other specific language for NLP application development.
Implementation of a specific task of language processing with autonomy using techniques of self-management and self-regulation.
Identify the underlying problem in a situation, gathering the necessary information and selecting the relevant elements for objective understanding.
Temary
1. Conceptos básicos de programación2. Funciones y clases
3. Estructuras de datos básicas
4. Librerías para la construcción y tratamiento de recursos lingüísticos
5. Aplicaciones avanzadas
Bibliography
Basic bibliography
Notebook for learning basic Pythonhttp://nbviewer.ipython.org/github/ehmatthes/intro_programming/blob/master/notebooks/syllabus.ipynb
Natural Language Processing in Python (http://www.nltk.org/book)
Analyzing Text with the Natural Language Toolkit. Steven Bird, Ewan Klein, and Edward Loper. O'Reilly Media, 2009
Advanced Topics in Humanities Programming with Python. https://github.com/sonofmun/ESU-2014
Referencias para los formatos KAF y NAF:
Representing linguistic information on text. KAF format. OpeNER project.
http://demo2-opener.rhcloud.com/welcome.action