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I am trying to annotate the vocabulary in the corpus.

  1. I have trained the word2vec model on the corpus

  2. I have grouped the words which are related based on the score as key as the first word as the key and remaining words as a list of 2-tuple of word and scores with respect to the key

example: 'coffee'---key values are

[('tea', 0.8139282),
 ('latte', 0.76456803),
 ('coffe', 0.7607962),
 ('lattes', 0.756057),
 ('starbucks', 0.7158153),
 ('espresso', 0.71386236),
 ('mocha', 0.69999266),
 ('coffees', 0.6816252),
 ('frappucino', 0.67192864),
 ('cuppa', 0.66720986),
 ('cappucino', 0.6664002),
 ('chai', 0.6623157),
 ('decaf', 0.65980726),
 ('frappuccino', 0.65150374),
 ('venti', 0.6486204),
 ('expresso', 0.6369579),
 ('macchiato', 0.6280453),
 ('scone', 0.62476856),
 ('sippy', 0.6236704),
 ('cappuccino', 0.61718297),
 ('iced', 0.6130485),
 ('hazelnut', 0.6023698),
 ('mug', 0.6004759),
'
'
'
'
'

as i know the coffee is releated to latte ,green_tea ,espresso,starbucks.. from the above data I would like to label each word as below

latte [COHYPO] green_tea [COHYPO] espresso [HYPO] Starbucks [RELATED] tim_horton [RELATED]

COHYPO-https://en.wiktionary.org/wiki/cohyponym

[HYPO] -https://en.wiktionary.org/wiki/hyponyme

[RELATED] -the word is repeated

[MORPHO]-Morphological variant (example :Computer and computers )

[Partof]- indicates that the annotated word is a part of the word of interest

Any suggestion or ideas by which I can approach this problem

  • Do you want a multi label classification (coffee = cohypo_2, hypo_5, etc) or just a mono label (coffee = cohypo_2) ? – amegnunsen Nov 28 '19 at 15:09
  • I want multilabel classification – Nuser Nov 28 '19 at 15:59
  • What is it your preferred programming language? – amegnunsen Nov 28 '19 at 16:53
  • I am trying to do this in python – Nuser Nov 28 '19 at 16:57
  • What do you mean by annotation ? interlinear gloss? graph network? ... – amegnunsen Nov 28 '19 at 17:38

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