Natural Language Processing Named Entity Recognition and Information Extraction 2

Question 1

What is dependency parsing in NLP?

Accepted Answer

Analyzing the grammatical structure of a sentence by establishing relationships between 'head' words and words that modify them

Answer

Dependency parsing produces a tree where each word is connected to its syntactic head by a labeled directed arc, revealing grammatical roles like subject and object.

Question 2

What is constituency parsing?

Accepted Answer

Analyzing a sentence into nested hierarchical phrases using a context-free grammar

Answer

Constituency parsing builds a parse tree that groups words into nested phrases (NP, VP, etc.) according to a phrase-structure grammar.

Question 3

What is semantic role labeling (SRL)?

Accepted Answer

Identifying the semantic roles of words or phrases with respect to a predicate, such as agent, patient, or instrument

Answer

SRL answers 'who did what to whom, how, when, and where' by labeling each argument of a verb with its semantic role relative to that predicate.

Question 4

What is open information extraction (OpenIE)?

Accepted Answer

Extracting relational triples (subject, relation, object) from text without a predefined ontology

Answer

OpenIE systems like AllenNLP's extract arbitrary (subject, relation, object) triples from sentences, enabling scalable knowledge acquisition without labeled training data.

Question 5

What is a knowledge graph in the context of NLP?

Accepted Answer

A structured representation of entities and their relationships stored as a graph of nodes and edges

Answer

Knowledge graphs (e.g., Wikidata, Freebase) store real-world facts as (entity, relation, entity) triples and power question answering, recommendation, and search systems.

Natural Language Processing Practice Test

Natural Language Processing Practice Test

Natural Language Processing Named Entity Recognition and Information Extraction 2