Collection of modules for feature extraction, Lesk algorithm and classification for the bachelor thesis titled "Disambiguating nominal prefixoid and suffixoid formations from compounds"
Requirements
Clone the repository
$ git clone https://github.com/darminspahic/affixoid-disambiguation.gitInstall requirements
$ pip install -r src/requirements.txtba-ss18/
├── data
│ ├── features (output path for FeatureExtractor.py)
│ ├── final (gold standard data)
│ ├── statistics (affixoid statistics)
│ └── wsd (data for Lesk)
│ └── sdewac2
│ ├── final (output path when splitting data)
│ └── sentences (parsed sentences from sketchengine)
├── res
│ ├── AffectiveNorms
│ ├── EmoLex
│ ├── fastText
│ ├── GermaNet
│ ├── PMI
│ ├── PolArtUZH
│ ├── SentiMerge
│ └── SentiWS
└── src
├── Classifier.py
├── config.ini
├── FeatureExtractor.py
├── requirements.txt
├── StatisticsExtractor.py
├── Wsd.py
└── modules
└── doctests
config.ini contains all the required settings for filenames and paths. The main modules FeatureExtractor.py, Wsd.py and Classifier.py are pre-configured to use files from the resources.
$ src/config.iniBefore extraction, set correct path to the file with normalized pmi values (due to size not in this package) sdewac_npmi.csv.bz2 in:
$ config.iniand run:
$ cd src/
$ python FeatureExtractor.pyBefore running the Word Sense Disambiguation module make sure that the GermaNet resource (available from the University of Tübingen) and pygermanet are installed. More info here
$ cd src/
$ python Wsd.pyResults from FeatureExtractor.py and Wsd.py will be written to files set in config.ini. Default values are ba-ss18/data/features/ and ba-ss18/data/wsd/. Classifier.py does not need GermaNet or PMI values, since the values are all available in the features folder. Classifier.py will load these features automatically and print results together with the most frequent sense baseline.
$ cd src/
$ python Classifier.pyTo obtain lexical coverage for affixoids from dlexdb, Wiktionary, GermaNet, SentiMerge and Duden
$ cd src/
$ python StatisticsExtractor.pyAgirre, Eneko, and Philip Edmonds. 2006. Word Sense Disambiguation: Algorithms and Applications (Text, Speech and Language Technology). Berlin, Heidelberg: Springer-Verlag.
Hamp, Birgit, and Helmut Feldweg. 1997. “GermaNet - a Lexical-Semantic Net for German.” Proceedings of the ACL Workshop Automatic Information Extraction and Building of Lexical Semantic Resources for NLP Applications.
Henrich, Verena, and Erhard Hinrichs. 2010. “GernEdiT - the Germanet Editing Tool.” Proceedings of the Seventh Conference on International Language Resources and Evaluation (LREC 2010), May. Valletta, Malta, 2228–35. http://www.lrec-conf.org/proceedings/lrec2010/pdf/264_Paper.pdf.
Pedregosa, F., G. Varoquaux, A. Gramfort, V. Michel, B. Thirion, O. Grisel, M. Blondel, et al. 2011. “Scikit-Learn: Machine Learning in Python.” Journal of Machine Learning Research 12: 2825–30.
Vapnik, Vladimir N. 1995. The Nature of Statistical Learning Theory. New York ; Berlin ; Heidelberg: Springer.
Copyright 2018 Darmin Spahic
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