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Evalution

Evalution is a collection of tools for the EVALuation models of semantic relations.

It consists of four components:

  • data extraction library:
    • A library to extract ngrams, patterns and frequencies from corpora.
  • datasets (data + api):
    • A dataset of semantic relations.
  • baseline:
    • A baseline model.
  • evaluation library:
    • A library for the automatic evaluation of semantic models.

Data extraction library

raw_data (data/)

test/corpora: Contains the corpora you want to extract the data from. They must be in csv format with the following header: WORD, LEMMA, POS, INDEX, PARENT, DEP.

test/wordlist: the list of words used to extract frequencies and ngrams.

test/patterns: a list of pairs used to extract patterns (string between the two target words).

corpus.py

This module contains a set of functions used to extract data from the corpora. The functions are optimized to extract a large number of words simultaneously.

The main functions, classes and methods are:

_open_corpus(fpath) preprocess (sanity check and concatenation) and yield a corpus as a file object.

Dataset(object) This object holds all the info about your data. It need a list of words or word pairs to be processed, and then it stores useful information about it.

When processing the files, the class allows us to pickle its state, so if the process is interrupted it can be resumed.

The three crucial attributes are:

  • ngrams an NgramCollection object (see below).
  • frequencies a dictionary of word frequencies, where k is a string representing a word, and v is a WordFrequency object.
  • patterns a dictionary of pattern frequencies, where k is a tuple of two words, and v is a PatternFrequency object.

TBF

dataset

The dataset is an SQLite database (also available in MySQL format) that contains information about the semantic relations. Some useful tables are described below.

allwordsenses - maps word id to their synsets. Words with the same sense are synonyms. Words with the same word_id are homographs.

  • word_id
  • language_id
  • wordsense_id

synsetrelation - maps a pair of synsets to a relation

  • sourcesynset_id
  • relation_id
  • targetsynset_id

word - list of all words

  • word_id
    • bank -> 347049
  • word_value

language - list of languages

  • language_id
    • en -> 6
  • language_value

relationname - list of relations

  • relationname_id
  • relationname_value

sysnetdomain - list of domains

  • synsetdomain_id
  • synsetdomain_value (e.g. agricolture, advertising, etc.)

Domain2synset - how likely is a synset to be in a domain

  • synset_id
  • domain_id
  • score

dataset API