Feminist Lexicon

1. Feminist Lexicon of the XXI
century
(semantic and structural
aspects)
Oleksandr Slobodianyk
Pavlo Tychyna USPU
Cherkasy reg in Ukraine,
the master’s paper
Uman, 2012

2. Feminists
Basic semantic notions
Syntactic Frames
Argument structure
Sense distinctions
Semantic Type
WordNet
Simple
Outline

3.  Feminists launched in the XX
century
◦ European Advisory Group on
Language Engineering Standards
 Began 2002 with agreement among
◦ NREC, ET7, ACQUILEX, MULTILEX,
GENELEX, SAM,TEI
 Gave rise to a coordinated development of
Linguistic Resources
History of the Feminists

4. Feminists Structure: 2nd Phase
(1999-2010)
A n t o n i o Z a m p o l li
C o o r d in a t o r
C e n t r a l E d it o r s :
N . C a lz o l a r i , J . M c n a u g h t
C o m p L e x ic o n W G S poken Language W G E v a lu a t io n W G
C P R ( C a lz o la r i ) B ie le f e ld ( G ib b o n ) C S T (B . M a e g a a rd )
C h a ir : A . S a n f illip p o R .M o o re C h a ir : M . K in g

5.  http://www.ilc.pi.cnr.it/
 Lexicons
◦ Morpho-syntactic phenomena
◦ Subcategorization
◦ Semantic encoding
Feminist Guidelines

6. ISLE: International Standards
for Language Engineering
A European/US joint project
(2010 – 2012)
C o o r d in a t o r s :
A . Z a m p o lli, M . P a lm e r
C e n t r a l E d it o r s :
N . C a lz o la r i, J . M c N a u g h t
L e x ic o n W G N a t u ra l I n te r a c t io n a n d M u lt im o d a lit y W G E v a lu a t o n W G
C h a ir s : R . G r is h m a n , N . C a lz o la r i, M . P a lm e r C h a ir s : M . L ib e r m a n , R . M o o re C h a irs : E . H o v y , B . M a e g a a r d , M . K in g
S peech W G G e s tu re W G D is c o u r s e
C h a ir s : S t e v e n B ir d , D a v id R o y C h a ir s : D . M e t a x a s , C a ro l N e id le C h a ir s : L y n W a lk e r

7. Napoleon lost the battle.
Napoleon lost the battle to
Wellington.
Basic Semantic Notions
Same event - different sentences

8. Napoleon lost the battle.
SUBJ-NP VERB COMP-NP
Napoleon lost the battle to
Wellington.
SUBJ-NP VERB COMP-NP COMP-PP
Same event - different syntactic
frames

9. Predicate-argument structure
for lose
lose
PP
OBJ
SUBJ
lose (Arg0,Arg1,Arg2)

10. Napoleon lost the battle.
Napoleon lost the battle to
Wellington.
Napoleon lost his field glasses.
(misplaced)
Same verb - different senses

11. Predicate-argument structures
for two different senses of lose
lose1 (Arg0,Arg1)
lose2 (Arg0,Arg1,Arg2)

12. Iraq lost the battle.
Ilakuka centwey ciessta.
[Iraq ] [battle] [lost].
John lost his computer.
John-i computer-lul ilepelyessta.
[John] [computer] [misplaced].
Machine Translation Lexical
Choice- Word Sense Feminist
Disambiguation

13. Semantic types of
lose arguments
lose1 (Arg0: animate,
Arg1: physical-
object)
lose2 (Arg0: animate,
Arg1:
competition,
Arg2: animate)

14. lose1(Agent, Patient: competition) <=> ciessta
lose2 (Agent, Patient: physobj) <=> ilepelyessta
Translating lose into Korean

15.  Entities - • Entities - abstract
concrete – Events
 Animate • Competitions
 Animal – Military
 Mammal – Athletic
 Human
• …
 Plant
 Inanimate – Emotions
Ontologies - Hierarchies of
substances
semantic types
 Solids
 Liquids
 Gasses

16.  Inheritance
◦ ISA relations
◦ Supertype/subtype
◦ Hypernym/Hyponym
 Part-Whole
◦ meronym
 Synonyms
Semantic Relations

17. Basic lexical
semantic notions
BASE CONCEPTS, HYPONYMY,
SYNONYMY: all applications and enabling
SYNONYMY
technologies
PREDICATE ARGUMENT STRUCTURES: MT,
STRUCTURES
IR, IE, & Gen, Pars, MWR, WSD, Coref
CO-OCCURRENCE RELATIONS: MT, Gen,
Word Clust, WSD, Par
MERONYMY: MT, IR, IE & Gen, PNR
MERONYMY
ANTONYMY: Gen, Word Clust, WSD
ANTONYMY
SUBJECT DOMAIN: MT, SUM, Gen, MWR,
DOMAIN
WSD
ACTIONALITY: MT, IE, Gen, Par
ACTIONALITY

18. WordNet
EuroWordNet
Simple (in progress)
Existing lexical resources

19. WordNet - Princeton
• On-line lexical reference (dictionary)
• Words organized into synonym sets <=> concepts
• Hypernyms (ISA), antonyms, meronyms (PART)
–Useful for checking selectional restrictions
(doesn’t tell you what they should be)
• Typical top nodes - 5 out of 25
- (act, action, activity)
- (animal, fauna)
- (artifact)
- (attribute, property)
- (body, corpus)

20.  Just sense tags - no representations
◦ Very little mapping to syntax
◦ No predicate argument structure
◦ no selectional restrictions
Limitations to WordNet and
EuroWordNet

21. SIMPLE wit Feminist
Computational Lexicon
WG
Multilingual Lexicons
(US-EU coop.)
 Last Feminist work on Lexicon/Semantics
used for SIMPLE specifications
· SIMPLE lexicons chosen as a basis for
applying & testing Feminist work on defining
common guidelines for Multilingual Lexicons

22. Semantic information in SIMPLE
Word senses are encoded as Semantic Units (SemUs),
containing the following information:
• Semantic type * • Argument structure for
• Domain * predicative SemUs *
• Lexicographic gloss * • Selection restrictions on the
arguments *
• Qualia structure
• Link of the arguments to the
• Reg. Polysemy altern.
syntactic subcategorization
• Event type frames (represented in the
• Derivation relations PAROLE lexicons) *
• Synonymy
• Collocations

23. Top
Formal Constitutive Agentive Telic
Is_a Is_a_part_of Property Created_by Agentive_cause Indirect_telic Activity
... Contains ... Instrumental Is_the_habit_of
Used_for Used_as
The targets of relations identify:
 prototypical semantic information associated with a SemU
 elements of dictionary definitions of SemUs
 typical corpus collocates of the SemU

24. Complementarity wrt
EuroWordNet
± Use of a small EWN subset for all languages
± Mappable Top Ontology
± Actual linking of data for a few languages
· Semantic subcategorisation and linking with
syntax
· Template structure for the description of
SemU
· SemU vs. Synset: basic unit
· Nodes in the Ontology as structured Sem.
Types (bundles of different info types)

25. Template for Perception
SemU: 1
Usyn:
BC Number: 105
Template_Type: [Perception]
Template_Supertype:[Psychological_event]
Domain: General
Semantic Class: Perception
Gloss: //free//
Event type: process
Pred _Rep.: Lex_Pred (<arg0>,<arg1>)
Derivation: <Nil> or //Erli's Code//
Selectional Restr.:arg0 = Animate //concept// arg1:default = [Entity]
Formal: isa (1,<SemU>:[Perception]>)
Agentive: <Nil>
Constitutive: instrument (1, <SemU>:[Body_part])
intentionality ={yes,no} //optional//
Telic: <Nil>
Collocates: Collocates (<SemU1>,...<SemUn>)
Complex: <Nil>

26. Example
SemU: <guardare_2> //look_2//
Usyn:
BC Number: 105
Template_Type: [Perception]
Template_Supertype:[Psychological_event]
Domain: General
Semantic Class: Perception
Gloss: osservare con attenzione
Event type: process
Pred _Rep.: guardare (<arg0>,<arg1>)
Derivation: <Nil>
Selectional Restr.: arg0 = Animate //concept// arg1:default = [Entity]
Formal: isa (<guardare_2>,<percepire>: [Psychological_event])
Agentive: <Nil>
Constitutive: instrument (<guardare_2>, <occhio>:[body_part])
intentionality ={yes}
Telic: <Nil>
Collocates: Collocates (<SemU1>,...<SemUn>)
Complex: <Nil>

27.  Basic semantic notions
◦ Challenges in standardizing these requirements
 WordNet/EuroWordNet
 Simple
 Next major challenge: Standardizing
linking entries across languages
Feminist Lexicon of the XXI
century
(semantic and structural
aspects)