POS Tagging and Corpus-Based Lexical ... - PAN Localization

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Sources and Suggested Readings Allen, J. 2004. Natural Language Understanding. Person Education, Singapore. Brill, E. 1992. A simple rule-based part-of-speech tagger. In Proceedings of the Third Conference on Applied Natural Language Processing, Italy. Brill, E. 1995. Transformation-Based Error-Driven Learning and Natural Language Processing: A Case Study in Parts-of- Speech Tagging. Computational Linguistics, 21-4. Brill, E. 1997. Unsupervised learning of Disambiguation Rules for Parts-of-Speech Tagging. In Natural Language Processing Using very Large Corpora. Kluwer Academic Press. Charniak, E. 1993. Statistical Language Learning. The MIT Press, Cambridge. Thurseday, June 23, 2005 POS Tagging PANLC 2005
Sources and Suggested Readings Harris, Z. 1962. String Analysis of Language Structure. Mouton and Co, The Hague. Jurafsky, D. and J. H. Martin. 2000. Speech and Language Processing. Prentice-Hall, New Jersy. Mahapatra, B. B. 2004. Hindi Verb Morphology. Ms. CFILT, IITB, INDIA. Manning, C. D. and H. Schiitze. 2002. Foundations of Statistical Natural Language Processing. The MIT Press. Marcus, M. P., B. Santorini, and M. A. Marcinkiewicz. 1993. Building a large annotated corpus in English: The Penn Treebank. Computational Linguistics, 19-2. Thurseday, June 23, 2005 POS Tagging PANLC 2005
Page 1 and 2:
Parts-of-Speech Tagging Rajat Kumar
Page 3 and 4:
An Ubiquitous Task Sequence label
Page 5 and 6:
Example (Words: Parts-of-Speech Tag
Page 7 and 8:
Basic Idea of POS Tagging To as
Page 9 and 10:
Linguistic Input: Parts of Speech (
Page 11 and 12:
Closed Class Types • Determiners
Page 13 and 14:
Open Class Types Nouns (Common
Page 15 and 16:
Tagset Design An appropriate
Page 17 and 18:
Penn Treebank POS Tags 36 + 12 1.
Page 19 and 20:
Penn Treebank POS Tags 37. # Pound
Page 21 and 22:
Verb forms in English Base VB -S VB
Page 23 and 24:
Methods to assign Tags Two common
Page 25 and 26:
The ENGTWOL Tagger (Voutilainen, 19
Page 27 and 28:
Adverbial-THAT Rule (informal) Giv
Page 29 and 30:
Stochastic Taggers Produce an o
Page 31 and 32:
Example Probabilities • P(V
Page 33 and 34: Transformation-based Rules Init
Page 35 and 36: Two Kinds of Rules Contextual Rul
Page 37 and 38: The Transformation Templates (non-l
Page 39 and 40: The Transformation Templates (lexic
Page 41 and 42: Transformations for Unknown Words
Page 43 and 44: Transformation-Based Learning (TBL)
Page 45 and 46: A Rule-based POS Tagger for Hindi
Page 47 and 48: Morphs and Morphemes The decompose
Page 49 and 50: Examples Free Morphemes • morphe
Page 51 and 52: Affixation prefix unknowingly stem
Page 53 and 54: Allomorphy Phonetically Conditione
Page 55 and 56: Inflection Inflectional morphology
Page 57 and 58: Derivational Affixes Some examples
Page 59 and 60: Feature Percolation Convention (FPC
Page 61 and 62: Feature Percolation Convention -2
Page 63 and 64: The Morphology-Syntax Interaction
Page 65 and 66: Morphological Analysis Two basic a
Page 67 and 68: Analytic Principles Principle 2
Page 69 and 70: Analytic Principles Principle 4
Page 71 and 72: Morpheme Analysis DOs • Identify
Page 73 and 74: Morpheme Analysis: Examples The fo
Page 75 and 76: Computational Issues Segmentation
Page 77 and 78: Sample Hindi Morphological Analysis
Page 79 and 80: Shoebox Demo Thurseday, June 23, 2
Page 81 and 82: PNGTAM information in Hindi Verbs
Page 83: Conclusion A Rule-based POS T
Page 87: Thank You Thurseday, June 23, 2005
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POS Tagging and Corpus-Based Lexical ... - PAN Localization

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