I wanted to work with the datasets WN18 and WN18RR that contain 18/11 relations from wordnet data.
The original datasets have the following form:
02174461 _hypernym 02176268
05074057 _derivationally_related_form 02310895
08390511 _synset_domain_topic_of 08199025
02045024 _member_meronym 02046321
01257145 _derivationally_related_form 07488875
...
I wanted to have the textual form of the entities. Only the wordnet offsets are given as entites, transforming them back is problematic cause they are ambiguous within the 4 datafiles from wordnet.
For example 01257145 _derivationally_related_form 07488875 has two offsets:
01257145 and 07488875.
| 01257145 | 07488875 | |
|---|---|---|
| ADJ | sensual.s.02 |
|
| ADV | ||
| NOUN | precession.n.02 |
sensuality.n.01 |
| VERB |
I transformed the dataset back to wordnet synsets by validating if the given relation holds on the ambiguous entities.
The transformed textual data then looks like this:
clangor.v.01 _hypernym sound.v.02
straightness.n.02 _derivationally_related_form straight.a.02
militia.n.01 _synset_domain_topic_of military.n.01
alcidae.n.01 _member_meronym pinguinus.n.01
sensual.s.02 _derivationally_related_form sensuality.n.01
You can load it into NLTK by executing
from nltk.corpus import wordnet as wn
wn.synset('sensual.s.02')