NPTEL Natural Language Processing Week 10 Assignment Answers 2025
1. Different phases of entity linking are –
A) Candidate Selection -> Reference Disambiguation
B) Reference Disambiguation -> Candidate Selection -> Mention Identify
C) Mention Identify – Candidate Selection – Reference Disambiguation
D) All of the above
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2. The text span s=”river occurs in 700 different Wikipedia articles.
c1 223
c2 161
C3 78
C4 31
No Link 207
Calculate the keyphraseness of “Sea”.
A) 0.232
B) 0.886
C) 0.688
D) 0.704
Answer :-
3. What is the commonness of (s, c3) in the above question?
A) 0.765
B) 0.389
C) 0.158
D) 0.910
Answer :-
4. Relevant feature/s for a supervised model for predicting the topics to be linked is/are:
A) Disambiguation Confidence
B) Relatedness
C) Link Probability
D) All of the above
Answer :-
5. Which of the following problem exists in bootstrapping technique for Information extraction are:
A) Sensitiveness towards the seed set
B) High precision
C) Less manual intervention
D) All of the above
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6. Which of the following is an advantage of unsupervised relation extraction:
A) Can work efficiently with small amount of hand-labeled data
B) Not easily generalizable to different relations
C) Need no training data.
D) Always perform better than supervised techniques.
Answer :-
7. Which of the following is not a Hearst’s Lexico Syntactic Patterns for automatic acquisition of hyponyms –
A) X or other Y
B) X and other Y
C) Y including X
D) X but not Y
Answer :-
8. Advantage of Distant supervision over bootstrapping method
A) Need more data
B) Less human effort
C) Can handle noisy data better
D) No Advantage
Answer :-
9. Consider a dataset with a very low number of relations – all of which are very important. For a relation extraction task on that dataset, which of the following is the most useful metric
A) Precision
B) Recall
C) Accuracy
D) F1-Score
Answer :-
10. What is KeyPhraseness (wikipedia)?
A) Number of articles that mention a key phrase divided by the number of wikipedia articles containing it.
B) Number of Wikipedia articles that use it as an anchor, divided by the number of articles that mention it at all.
C) Number of articles that mention a key phrase times by the number of wikipedia articles containing it.
D) Number of Wikipedia articles containing the key phrases times by number of articles mentioning it.
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