Onto.PT: Towards the Automatic Construction of a Lexical Ontology ...

30 Chapter 3. Related Work
ple relations like {car ← Modifier ← wheel} but also paths of length two, like
{car → Hypernym → vehicle → Part → wheel}, and longer. Each path is automatically
weighted according to its salience. Figure 3.2 shows the ten top-weighted
paths from bird to parrot.
1. bird ← Hyp ← parrot
2. bird → Mod → parrot
3. bird → Equiv → parrot
4. bird ← Tsub ← include → Tobj → parrot
5. bird → Attrib → flightless ← Attrib ← parrot
6. bird ← Tsub ← deplete → Tsub → parrot
7. bird → PrepRel(as) → kea → Hyp → parrot
8. bird ← Hyp ← macaw → Equiv → parrot
9. bird → PrepRel(as) → species → PrepRel(of) → parrot
10. bird → Attrib → flightless ← Attrib ← kakapo → Hyp → parrot
FrameNet
Figure 3.2: Ten top-weighted paths from bird to parrot in Mindnet.
Berkeley FrameNet (Baker et al., 1998) is a network of semantic frames (Fillmore,
1982), manually extracted from a systematic analysis of semantic patterns in corpora
text. Each frame describes an object, a state or an event, and corresponds to a
concept. The frame may be connected to other frames, by means of syntactic and
semantic relations of the lexical item that describes the concept. Besides Inheritance,
which is more or less the hypernymy relation, the represented semantic relations
include Subframe, Inchoative of, Causative of, Precedes, Using and See also.
A frame can be conceived as the description of a situation with properties, participants
and/or conceptual roles. An example of a semantic frame is presented in
Figure 3.3 – the frame transportation is within the domain motion, which provides
the elements mover(s), means of transportation and paths and can be described in
one sentence as: mover(s) move along path by means.
VerbNet
VerbNet (Schuler, 2006) is a verb lexicon, compatible with WordNet, with explicit
syntactic and semantic information. Verbs are organised hierarchically into
Levin (1993) classes. Each class of verbs is characterized by syntactic frames, semantic
predicates and a list of typical verb arguments. The verb classes use several thematic
roles, namely: Actor, Agent, Asset, Attribute, Beneficiary, Cause, Location,
Destination, Source, Experiencer, Extent, Instument, Material, Product, Patient,
Predicate, Recipient, Stimulus, Theme, Time, and Topic. Verbs in VerbNet are
mapped to their corresponding WordNet synsets and FrameNet frames. Figure 3.4
illustrates VerbNet with the entry for the class Hit-18.1.