A python port of ADW [1].

• Python 2.x
• NLTK, with the WordNet corpus
• Semantic Signatures database (see Installation)
• Offset2ID map (see Installation)

1. Download the original Semantic Signatures database (for all the 118K concepts in WordNet 3.0, size ~ 1.4 GB) using the following link:

   http://lcl.uniroma1.it/adw/ppvs.30g.5k.tar.bz2

2. Extract the folder ppvs.30g.5k from the downloaded tarball:

   $ tar zxf ppvs.30g.5k.tar.bz2

3. adwpy.config expects this database (a) to be called ‘ppvs’ and (b) to be located in the adwpy/data/ directory. You could either move the downloaded folder to the expected location:

   $ mv ppvs.30g.5k adwpy/data/ppvs

   Or create a symlink:

   $ cd adwpy/data $ ln -s /path/to/ppvs.30g.5k ppvs

   Or edit adwpy.config.py to point to your prefered location.

4. Similarly with offset2ID.map.tsv from the ADW github page:

   https://raw.githubusercontent.com/pilehvar/ADW/master/resources/offset2ID.map.tsv

   The default location is also in adwpy/data:

   $ cd adwpy/data $ ln -s /path/to/offset2ID.map.tsv

adwpy ports the two disambiguation methods and three Semantic Signature comparison measures described in Pilehvar et al., 2013 [2], and implemented in [1]:

• Disambiguation methods:
  • NONE (i.e., no disambiguation)
  • ALIGNMENT_BASED (i.e., alignment-based disambiguation)
• Semantic Signature comparison measures
  • Cosine
  • WeightedOverlap
  • Jaccard

The only input format supported by adwpy is “surface text”.

The main front-end function in the library is api.pair_similarity. ADWTest.py gives an example of this function in use. Essentially:

dm = config.DisambiguationMethod.ALIGNMENT_BASED
sc = config.SignatureComparison.WEIGHTED_OVERLAP
score = pair_similarity(text1, text2, dm, sc)

Where score is a floating point number between 0.0 and 1.0.

[1] ADW https://github.com/pilehvar/ADW

[2] M. T. Pilehvar, D. Jurgens and R. Navigli. Align, Disambiguate and Walk: A Unified Approach for Measuring Semantic Similarity. Proceedings of the 51st Annual Meeting of the Association for Computational Linguistics (ACL 2013), Sofia, Bulgaria, August 4-9, 2013, pp. 1341-1351.