Author Topic: Relation Extraction  (Read 124 times)

Offline Nazia Nishat

  • Full Member
  • ***
  • Posts: 132
  • Test
    • View Profile
Relation Extraction
« on: July 13, 2018, 01:01:49 PM »
Many NLP applications require understanding relations between word senses: synonymy, antonymy,hyponymy, meronymy. WordNet is machine-readable database of relations between word senses, and an indispensable resource in many NLP tasks.
But WordNet is manually constructed, and has many gaps!
In WordNet 3.1
insulin
progesterone
Not in WordNet 3.1
leptin
pregnenolone

Relation extraction: 5 easy methods
1. Hand-built patterns
2. Bootstrapping methods
3. Supervised methods
4. Distant supervision
5. Unsupervised methods


Source:https://web.stanford.edu/class/cs224u/materials/cs224u-2016-relation-extraction.pdf
Wordnet:http://wordnetweb.princeton.edu/perl/webwn

Offline iftekhar.swe

  • Full Member
  • ***
  • Posts: 144
  • মানুষ তার স্বপ্নের সমান বড়
    • View Profile
    • DIU_SWE Faculty
Re: Relation Extraction
« Reply #1 on: September 06, 2018, 03:28:08 PM »
thanks for sharing
_________________________
MD. IFTEKHAR ALAM EFAT
Sr. Lecturer
Department of Software Engineering, FSIT
Daffodil International Univeristy

Offline s.arman

  • Sr. Member
  • ****
  • Posts: 258
  • Test
    • View Profile
Re: Relation Extraction
« Reply #2 on: April 16, 2019, 07:55:51 PM »
Thanks for sharing