R23
CSE · 3-2
✓ VERIFIED VS. PUBLISHED SYLLABUS 2026-07-09
Natural Language Processing
JNTUK R23 · CSE · semester 3-2 · syllabus
This JNTUK R23 professional elective is listed for Computer Science and Engineering (CSE). It is listed in semester 3-2. It carries 3 credits. The published coverage runs across 5 units, from Introduction through Discourse Analysis and Lexical Resources.
Verified vs. published syllabus
Checked 9 Jul 2026
SOURCE DOCKET
Published evidence
✓ Verified
Checked 9 Jul 2026
Record 5 published units
Verification scope Subject name, credits, unit-wise syllabus, and course outcomes are sourced directly from JNTUK's own official R23 course structure and syllabus document, not an autonomous college's adaptation.
5 units, from Introduction to Discourse Analysis and Lexical Resources. Tick off units as you cover them — your progress stays on this device.
Unit-wise syllabus
0 / 5 COVERED
UNIT 01 — Introduction
Origins and challenges of NLP; language modeling: grammar-based LM, statistical LM · Regular expressions and finite-state automata · English morphology; transducers for lexicon and rules; tokenization · Detecting and correcting spelling errors; minimum edit distance
UNIT 02 — Word Level Analysis
Unsmoothed N-grams; evaluating N-grams; smoothing, interpolation and backoff · Word classes and part-of-speech tagging · Rule-based, stochastic and transformation-based tagging; issues in PoS tagging · Hidden Markov and maximum entropy models
UNIT 03 — Syntactic Analysis
Context-free grammars, grammar rules for English, treebanks, normal forms for grammar · Dependency grammar; syntactic parsing, ambiguity, dynamic programming parsing · Shallow parsing; probabilistic CFG, probabilistic CYK, probabilistic lexicalized CFGs · Feature structures and unification of feature structures
UNIT 04 — Semantics and Pragmatics
Requirements for representation; first-order logic; description logics · Syntax-driven semantic analysis; semantic attachments · Word senses, relations between senses, thematic roles, selectional restrictions · Word sense disambiguation: supervised, dictionary & thesaurus, bootstrapping methods · Word similarity using thesaurus and distributional methods
UNIT 05 — Discourse Analysis and Lexical Resources
Discourse segmentation and coherence · Reference phenomena; anaphora resolution using Hobbs and Centering algorithms; coreference resolution · Resources: Porter stemmer, lemmatizer, Penn Treebank, Brill's tagger · WordNet, PropBank, FrameNet, Brown Corpus, British National Corpus (BNC)