This file briefly describes how the alignment process from WordNet 1.6 to WordNet 3.0 was carried out, leading to the creation of the file sp_mapping.csv, which will ultimately be used as the basis for aligning occurrence files with WordNet 3.0 whenever necessary.

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>> DESCRIPTION
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The alignment process consists of two steps:

# STEP 1)
=========
Following the proposal by Erik Kafe, we align the synset_Id's of WordNet 1.6 with their corresponding synsets in WordNet 3.0 using the concept of sense_key (an index that identifies the sense of a word and remains stable across different versions of WordNet).

We start from the files index_sense16 and index_sense30, which allow us to relate the synset_Id's of both versions through a sense_key, in order to obtain a table indicating, for a given synset_Id in WN16, which synset_Id in WN30 corresponds to it.

The program 1-map_wn16_to_wn30.py sequentially scans the file index_sense16 and generates an intermediate file called rough_mapping.csv with the structure:

			pos,synset_Id16,bag

where bag is a list whose elements are pairs of the form: (synset_Id30, lemma_list)

where lemma_list is a list containing the lemmas associated with the synset_Id16 that correspond to the given synset_Id30.

Once the generation of rough_mapping.csv is complete, the program analyzes it and produces several files:

* Records where the bag field is a list with a single element are stored in the file mapping_WN16_to_WN30.csv.

* Records where the bag field is an empty list are stored in the file no_map.csv.

* Records where the bag field is a list with more than one element are stored in the file split.csv.

* When the synset_Id16 field of several records points to the same synset_Id30, they are stored in a record of the file merge.csv.

File name                  : Structure
-------------------------------------------------------------------
mapping_WN16_to_WN30.csv   : Index,synset_Id16,synset_Id30,pos
no_map.csv                 : pos,synset_Id16,bag(= no_map)
split.csv                  : pos,synset_Id16,bag(= list with several target synset_Id30)
merge.csv                  : Index,pos,synset_Id30,synset_Id16_list

Although the information contained in these files may be useful, it has not been used in the development of the present work.

# STEP 2)
=========
In this step, the starting point is the file rough_mapping.csv, and the file wn_MCR_s.csv, which contains various types of lexical information extracted from the MCR Spanish WordNet databases, is used.

The structure of the file wn_MCR_s.csv is:

			Index, Synset, W Num, Word, Type, Sense, Tag Count

The program 2-sp_convert_mapping.py generates a file called sp_mapping.csv with the same structure as rough_mapping.csv, but with the English lemma lists replaced by lists of Spanish lemmas corresponding to the synsets in the file wn_MCR_s.csv.

As mentioned above, the file sp_mapping.csv is the one used in the rest of the work.

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>> PROGRAM EXECUTION
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The macro script_alineamiento_WN16_a_WN30.sh simplifies the execution of the programs. It assumes that both the programs and the input files index_sense16, index_sense30, and wn_MCR_s.csv reside in the same working directory.

