1. The contribution of NLP Corpus processing Ontologies and terminologies
Kivik 2013
NLP. Corpus processing, Ontologies

2. NLP. Corpus processing, Ontologies
What is NLP?
Natural Language Processing
natural language vs. computer languages
Other names
Computational Linguistics
emphasizes scientific not technological
Language Engineering
Language Technology
Kivik 2013
NLP. Corpus processing, Ontologies

3. NLP and linguistics L I N N L G P supply ideas interpret results
test theories
expose gaps
plus turn into technology
Kivik 2013
NLP. Corpus processing, Ontologies

4. Example: regular morphology
LINGUISTICS:
Rules: stems -> inflected forms
NLP:
program the rules
apply rules to a lexicon of stems
Is the output correct? Errors?
refine the theory
Needed for: web search, spell-checkers, machine translation, speech recognition systems etc.
Kivik 2013
NLP. Corpus processing, Ontologies

5. NLP. Corpus processing, Ontologies
Applications
web search
Basic search
Filtering results
spelling and grammar checking
machine translation (MT)
talk to computers
speech processing as well
information extraction
finding facts in a database of documents
answering questions
Kivik 2013
NLP. Corpus processing, Ontologies

6. How can NLP make better dictionaries?
By pre-processing a corpus:
tokenization
sentence splitting
lemmatization
POS-tagging
parsing
Each step builds on predecessors
Kivik 2013
NLP. Corpus processing, Ontologies

7. NLP. Corpus processing, Ontologies
Tokenization
“identifying the words”
from:
he didn't arrive.
to: He
did
n’t
arrive .
Kivik 2013
NLP. Corpus processing, Ontologies

8. Automatic tokenization
Western writing systems
easy! space is separator
Chinese, Japanese, some other writing systems
do not use word-separator
hard
like POS-tagging (below)
Kivik 2013
NLP. Corpus processing, Ontologies

9. Why isn't space=separator enough (even for English)?
what is a space
linebreaks, paragraph breaks, tabs
Punctuation
characters do not form parts of words but may be attached to words (with no spaces)‏
brackets, quotation marks
Hyphenation
is co-op one word or two? is well-managed?
Kivik 2013
NLP. Corpus processing, Ontologies

10. NLP. Corpus processing, Ontologies
Sentence splitting
to:
<s> He
did
n’t
arrive .
</s>
“identifying the sentences”
from:
he didn't arrive.
to: He
did
n’t
arrive .
Kivik 2013
NLP. Corpus processing, Ontologies

11. NLP. Corpus processing, Ontologies
Lemmatization
Mapping from text-word to lemma
help (verb)‏
text-word to lemma
help help (v)‏
helps help (v)‏
helping help (v)‏
helped help (v) .
Kivik 2013
NLP. Corpus processing, Ontologies

12. NLP. Corpus processing, Ontologies
Lemmatization
Mapping from text-word to lemma
help (verb) help (noun), helping (noun)‏
text-word to lemma
help help (v), help (n)‏
helps help (v), helps (n)**
helping help (v), helping (n)‏
helped help (v)
helpings helping (n)‏
**help (n): usually a mass noun, but part of compound home help which is a count noun, taking the "s" ending. .
Kivik 2013
NLP. Corpus processing, Ontologies

13. NLP. Corpus processing, Ontologies
Lemmatization
Dictionary entries are for lemmas
Match between text-word and dictionary-word
lemmatization
Kivik 2013
NLP. Corpus processing, Ontologies

14. NLP. Corpus processing, Ontologies
Lemmatization
Searching by lemma
English: little inflection
French: 36 forms per verb
Finno-Ugric: 2000.
Not always wanted:
English royalty
singular: kings and queens
plural royalties: payments to authors
Kivik 2013
NLP. Corpus processing, Ontologies

15. Automatic lemmatization
Write rules:
if word ends in "ing", delete "ing";
if the remainder is verb lemma, add to list of possible lemmas
If detailed grammar available, use it
full lemma list is also required
Often available from dictionary companies
Kivik 2013
NLP. Corpus processing, Ontologies

16. Part-of-speech (POS) tagging
He PNP pers pronoun
did VVD past tense verb
n’t XNOT not
arrive VV base form of verb
. C punctuation
</s>
“identifying parts of speech”
from:
he didn't arrive.
to: … .
Kivik 2013
NLP. Corpus processing, Ontologies

17. NLP. Corpus processing, Ontologies
Tagsets
The set of part-of-speech tags to choose between
Basic: noun, verb, pronoun …
Advanced: examples - CLAWS English tagset
NN2 plural noun
VVG -ing form of lexical verb
Based on linguistics of the language.
Kivik 2013
NLP. Corpus processing, Ontologies

18. NLP. Corpus processing, Ontologies
POS-tagging: why?
Use grammar when searching
Nouns modified by buckle
Verbs that buckle is object of
Kivik 2013
NLP. Corpus processing, Ontologies

19. NLP. Corpus processing, Ontologies
POS-tagging: how?
Big topic for computational linguistics
well understood
taggers available for major languages
Some taggers use lemmatized input, others do not
Methods
constraint-based: set of rules of the form
if previous word is "the" and VERB is one of the possibilities, delete VERB
Statistical:
Machine learning from tagged corpus
Various methods
Ref: Manning and Schutze, Foundations of Statistical Natural Language Processing, MIT Press 1999.
Kivik 2013
NLP. Corpus processing, Ontologies

20. NLP. Corpus processing, Ontologies
Parsing
Find the structure:
Phrase structure (trees)‏
The cat sat on the mat
Dependency structure (links)‏
The cat sat on the mat
Kivik 2013
NLP. Corpus processing, Ontologies

21. NLP. Corpus processing, Ontologies
Automatic parsing
Big topic
see Jurafsky and Martin or other NLP textbook
Many methods too slow for large corpora
Sketch Engine usually uses “shallow parsing”
Patterns of POS-tags
Regular expressions
Kivik 2013
NLP. Corpus processing, Ontologies

22. NLP. Corpus processing, Ontologies
Summary
What is NLP?
How can it help?
Tokenizing
Sentence splitting
Lemmatizing
POS-tagging
Parsing
Kivik 2013
NLP. Corpus processing, Ontologies

23. Ontologies and Terminology
and how they relate to lexicography
Kivik 2013
NLP. Corpus processing, Ontologies

24. NLP. Corpus processing, Ontologies
Terminology
Contains terms
for the objects and concepts in a domain
organized according to relations between objects
Different language
Same objects, so
Same organization
Different terms
Kivik 2013
NLP. Corpus processing, Ontologies

25. Ontology Artificial Intelligence Like terminology with reasoning
Tweety is-a swallow
A swallow is-a bird
Birds fly
Inference
Tweety flies
the rationalist dream of automated reasoning
Bird
flies
swallow
robin …
Tweety
Kivik 2013
NLP. Corpus processing, Ontologies

26. NLP. Corpus processing, Ontologies
Ontology
Chris is-a dentist
Chris has-practice in Lancing
Chris works 9am-3pm Mon-Fri …
You live-near Lancing
You want-to-visit dentist
You are-available …
Inference
Appointment, you, Chris, Lancing, 10am, Thursday
Kivik 2013
NLP. Corpus processing, Ontologies

27. NLP. Corpus processing, Ontologies
Items in an ontology
Defined by relations in ontology
Labelled (only) by words/phrases in various languages X1
EN: bird
FR: oiseau X2
EN: swallow
FR: hirondelle …
Ontology/things: language independent
Kivik 2013
NLP. Corpus processing, Ontologies

28. NLP. Corpus processing, Ontologies
Mismatches and gaps Y1
EN: body parts
SP: … Y2
SP: dedo Y5
EN: arm
SP: bras Y3
EN: finger Y4
EN: toe
Kivik 2013
NLP. Corpus processing, Ontologies

29. NLP. Corpus processing, Ontologies
Thesaurus (eg Roget)‏
Looks like a simple ontology
hierarchy only
supports inference?
usually fudged
Language independent?
Kivik 2013
NLP. Corpus processing, Ontologies

30. NLP. Corpus processing, Ontologies
WordNet
Princeton Univ project, from ca 1990
Thesaurus
Synonym sets or synsets
Hyponyms/hyperonyms, antonyms, part-of, other lexical relations
Free, online and available for download
Very widely used
Replicated for many languages, Global WN Assn
Kivik 2013
NLP. Corpus processing, Ontologies

31. NLP. Corpus processing, Ontologies
Lexicon/dictionary
About words
Organized by words
Language specific
Kivik 2013
NLP. Corpus processing, Ontologies

32. Rationalists Empiricists
Structure
Depth
Logic
Semantic Web
Terminology
Data
Breadth
Statistics
Google
Lexicography
Kivik 2013
NLP. Corpus processing, Ontologies

33. Terminology Lexicography
What is the thing called
in languages x, y, z
What kind of thing is it
Is-a link
Its place in ontology
Well-structured hierarchy
How does the word behave?
what does it denote?
Where does it occur?
Kivik 2013
NLP. Corpus processing, Ontologies

34. NLP. Corpus processing, Ontologies
Synthesis
Thesis
Ontology, terminology, taxonomical lexicography
Semantic web, Roget, WordNets
Antithesis
Corpus lexicography
Synthesis: integrating
language-independent structure
language-specific word/phrase behaviour
Corpus-based terminology
FrameNet
Kivik 2013
NLP. Corpus processing, Ontologies

35. NLP. Corpus processing, Ontologies
Summary
words
Lexicon
Thesaurus/Terminology
Ontology
things
Kivik 2013
NLP. Corpus processing, Ontologies