Content
Overview
Concepts are the basic unit to enter lexicographic data for GermaNet. Concepts are
described as synsets. Each synset consist of a list of lemmas or lexical units denoting
the lexical realizations of the concept described. Note, that a list of synonyms can
consist of only one element.
There are two types of relations, conceptual relations denote relations that hold
for the full concept, not only for one of its synonyms. Lexical relations hold between
lexical realizations (synonyms, lemmas), one frequent lexical relation is for example
the antonymy.
GermaNet covers all relations which are defined for WordNet®, except for the
'similar to' relation for adjectives, which is replaced by the
hyperonymy/hyponymy relation in GermanNet (see description of
adjectives for details).
Some of them (like 'entails') are used less often in GermaNet, others (like
'cause to') will be used more frequently (see description of verbs for details).
One major difference to WordNet® is that cross-classification
(multiple inheritence) is explicitly allowed in GermaNet and lexicographers are
encouraged to make ample use of it whenever appropriate.
This section is intended to list all the relations together with their definition,
restrictions in use, and notes on the current status of their implementation.
Legend
- Valid Class N: is the relation valid for nouns?
- Valid Class A: is the relation valid for adjectives?
- Valid Class V: is the relation valid for verbs?
Conceptual Relations
Hyperonymy/Hyponymy
According to EuroWordNet, the "denotation of a hyponym is
never equal to the denotation of a hyperonym, i.e. it must be a proper
subset. There must be multiple co-hyponyms to result in a genuine
hyponomy relation." It is assumed that the hyperonym (more
general) may substitute the hyponym (less general) in a given context,
but not the other way round.
Test (EuroWordNet) for verbs:
Verb synset X is hyponym of verb synset Y and verb synset Y is a hyperonym
of verb synset X if the following test sentences can be answered accordingly:
X is Y + AdvP/AdjP/NP/PP.
('To run' is 'to go' fast.)
|
yes |
Y is X + AdvP/AdjP/NP/PP.
('To go' is 'to run' fast.)
|
no |
Test (EuroWordNet) for nouns:
Attention has to be payed, since this test can also be used for
synonymy. Therefore a second test for species, kinds, races, and
brands has been developed.
Test 1 (also for synonymy):
X is a hyponym/synonym of Y and Y is a hyperonym/synonym of X if the following test sentences apply:
An X is a Y with specific characteristics.
(A car is a vehicle with specific characteristics.)
It is an X and thus also a Y.
(It is a car and thus also a vehicle.)
If it is an X, it has to be also a Y.
(If it is a car...)
|
yes |
Inversion of the above sentences
(A vehicle is a car with specific characteristics.)
(It is a vehicle and thus also a car.)
(If it is a vehicle ...)
|
no |
Test 2 (for species, kinds, races, and brands):
Note that this test cannot be used for synonymy.
X is a kind/a type/a race/a species/a brand of Y.
(A car is a kind of vehicle.)
|
yes |
Inversion of the above sentence
(A vehicle is a kind of car.)
|
no |
Meronymy/Holonymy
This relation in general only applies to concrete nouns which are interpreted generically (EuroWordNet 1996). According to EuroWordNet, part-whole relations come in inverse pairs, i.e. as holonymy and meronymy.
Test (EuroWordNet) :
X has a holonym Y and Y has a meronym X if
(an) X constitutes a part of (a) Y
(a) Y has (an) X.
|
yes |
Inversion of the above sentences |
no |
Causation
This pointer indicates the causation relation especially between verbs and adjectives.
See also Semantic Relations between Verbs
Association
This is a dummy pointer without a clear definition that is best
characterized as "is related to". See also Semantic Relations between Verbs
Lexical Relations
Synonymy
The following text passages are taken from the EuroWordNet General Document (edited by Piek Vossen, University of Amsterdam, and published in July 2002;
it is online available):
Synonymy is the basis for the organization of the database in synsets.
Miller and Fellbaum (1990) suggested a notion of synonymy, namely 'semantic similarity', which is defined as:
“two expressions are synonymous in a linguistic context C if the substitution of one for the other in C does not alter the truth value” (Miller et al., 1990).
From this we can derive the following tests for synonymy between nouns and verbs respectively:
Test 1: Synonymy between nouns
if it is (a/an) X then it is also (a/an) Y
if it is (a/an) Y then it is also (a/an) X
Example:
if it is a fiddle then it is a violin
if it is a violin then it is a fiddle
synset variants {fiddle, violin}
Test 2: Synonymy between verbs
If something/someone/it Xs then something/someone/it Ys
If something/someone/it Ys then something/someone/it Xs
If something/someone/it begins then something/someone/it starts
If something/someone/it starts then something/someone/it begins
synset variants: {begin, start}
Antonymy
Test (EuroWordNet) for Verbs:
In EuroWordNet antonymy is a relation between variants,
i.e. between elements of the same synset: Synset variant X is an antonym of synset variant Y if X is the opposite of Y.
Test sentences:
If sth./sb. X-s, he/she/it does not Y.
(If she borrows sth., she does not lend it.)
|
yes |
If sth./sb. Y-s, he/she/it does not X.
(If she lends sth., she does not borrow it.)
|
yes |
The following conditions have to apply for this relation:
- X and Y share the same hyperonym, thus they are elements of a co-hyponym synset (this prevents, e. g., that verbs like eat and sleep are designated as antonyms).
- There is a hyperonym of X, which is the opposite of a hyperonym of Y.
- Both verbs involve the same participants, which play, however, different roles in the situations (i.e. states, events or processes) that are described by these verbs (example: give and receive are antonyms because the indirect object of give , i.e. the addressee, who is involved in the event, is subject of receive ).
EuroWordNet further assumes a relation called near_antonymy
which applies to entire synsets, i.e. the antonymy relation
holds between all members of the synset. Besides this, the test is the
same as for antonymy (including the three conditions).
Test (EuroWordNet) for Nouns
Antonymy and near_antonymy are also distinguished for nouns. The
test is simpler than for verbs however:
X is an antonym of Y and Y is an antonym of X if the following test sentences apply:
X and Y are both a kind of Z, but X is the opposite of Y.
(i.e. Z is a hyperonym of X and Y.)
(Love and hate are both a kind of emotion, but love is the opposite of hate.) |
yes |
Inversion of the above sentence
(Hate and love are both a kind of emotion, but hate is the opposite of love.)
|
yes |
As for verbs, the condition that Z is a hyperonym of both X and Y is
necessary in order to guarantee that the antonymy relation is stated in
a reasonable, competitive denotational range.
Pertonymy
The lexical relation pertonymy combines adjectives derived from a noun with their nominal base. The noun forms the basis of
the adjective and determines its meaning (e.g. the adjective finanziell (financial) is derived from the noun Finanzen (finance)).
Participle
A subgroup of adjectives corresponds formally with the participle of a verb.
Their semantic refers to the semantic of the underlying verb, but additionally
they show to a different extent idiosyncratic semantic features. In those cases
where the semantics of the underlying verb is in a significant way relevant for
the interpretation of the participle adjective, there is a relation from the adjective
to the respective verb. For example, ergreifend, ergriffen refer to the verb ergreifen
in the sense of having an emotional effect on someone (eine emotionale Wirkung auf jemanden haben).
Compound Relations
Compound relations specify the semantic relation which can be established between a compound and its modifier.
The inventory of those relations is based on the results of a project in the
Collaborative Research Centre (SFB) 833 "The Construction of Meaning: The Dynamics and Adaptivity of Linguistic Structures" at the University of Tübingen:
"Corpus-based Semantic Composition Models for Phrases".
In this project a complex annotation scheme was developed to characterize the semantic relation between the modifier and the head of a given noun compound.
We adapted this scheme and reformulated it as a relation between modifier and compound.
The following examples illustrate some possible relations of compounds with the head ‚Haus’:
Holzhaus (wooden house) [has_material] Holz (wood)
Gästehaus (guest house) [has_user] Gast (guest)
Autohaus (car dealership) [has_goods] Auto (car)
Baumhaus (tree house) [has_location] Baum (tree)
This table shows all compound relations with an example of each:
GN-relation |
Example |
has_active_usage |
Schlafwagen has_active_usage Schlaf |
has_occasion |
Geburtstagsgeschenk has_occasion Geburtstag |
has_attribute |
Zauberland has_attribute Zauber |
has_appearance |
Kugelfisch has_appearance Kugel |
has_construction_method
|
Blockhütte has_construction_method Block
|
has_container
|
Dosenmilch has_container Dose
|
is_container_for
|
Mokkatasse is_container_for Mokka
|
has_consistency_of
|
Panzerglas has_consistency_of Panzer
|
has_component
|
Chlorwassser has_component Chlor
|
has_owner
|
Metzgerladen has_owner Metzger
|
is_owner _of
|
Hauseigentümer is_owner _of Haus
|
has_function
|
Grenzzaun has_function Grenze
|
has_manner_of_functioning
|
Sonnenuhr has_manner_of_functioning Sonne
|
has_origin
|
Ackersalat has_origin Acker
|
has_production_method
|
Pfannkuchen has_production_method Pfanne
|
has_content
|
Bilderbuch has_content Bild
|
has_no_property
|
Maultier has_no_property Maul
|
has_habitat
|
Bachforelle has_habitat Bach
|
has_location
|
Almhütte has_location Alm
|
is_location_of
|
Schlossberg is_location_of Schloss
|
has_measure
|
Literflasche has_measure Liter
|
is_measure_of
|
Blutzuckerspiegel is_measure_of Blutzucker
|
has_material
|
Holzhaus has_material Holz
|
has_member
|
Kinderchor has_member Kind
|
is_member_of
|
Marinesoldat is_member_of Marine
|
has_diet
|
Ameisenbär has_diet Ameise
|
is_diet_of
|
Katzenfutter is_diet_of Katze
|
has_eponym
|
Panflöte has_eponym Pan
|
has_user
|
Taucherbrille has_user Taucher
|
has_product
|
Autofabrik has_product Auto
|
is_product_of
|
Spinnennetz is_product_ofSpinne
|
has_prototypical_holder
|
Altartuch has_prototypical_holderAltar
|
is_prototypical_holder_for
|
Kleiderbügelis_prototypical_holder_forKleid
|
has_prototypical_place_of_ usage
|
Gartenbank has_prototypical _place_of_usage Garten
|
has_relation
|
Bankdirektor has_relation Bank
|
has_raw_product
|
Apfelsaft has_raw_product Apfel
|
has_other_property
|
Jägerzaun has_other_property Jäger
|
is_storage_for
|
Bildarchiv is_storage_for Bild
|
has_specialization
|
Augenarzt has_specialization Auge
|
has_part
|
Gelenkbus has_part Gelenk
|
is_part_of
|
Autodach is_part_of Auto
|
has_topic
|
Sportzeitung has_topic Sport
|
is_caused_by
|
Regenbogen is_caused_by Regen
|
is_cause_for
|
Schauerroman is_cause_for Schauer
|
is_comparable_to
|
Satellitenstadt is_comparable_to Satellit
|
has_usage
|
Handelsschiff has_usage Handel
|
has_result_of_usage
|
Wärmflasche has_result_of_usage Wärme
|
has_purpose_of_usage
|
Autoschlüssel has_purpose_of_usage Auto
|
has_goods
|
Blumenladen has_goods Blume
|
has_time
|
Abendzeitung has_time Abend
|
is_access_to
|
Haustür is_access_to Haus
|
has_ingredient
|
Obstkuchen has_ingredient Obst
|
is_ingredient_of |
Kaffeemilch is_ingredient_of Kaffee |