Events
States
Jackendoff's conceptual structures are built up using constituents in the ontology. Each constituent can be decomposed into function-argument structure. Functions impose conceptual constraints on the nature of and relations between function argument(s), which are themselves required to correspond to conceptual constituents. So, for example, a Place may be characterised as Place-function(Thing) and a Path might be characterised as Path-function(Place). Jackendoff seeks to identify functions which explain grammatical patterns of combination, using the ontology as a reference point. The existence of such an ontology provides a starting point for the identification of generalisations about how words can combine to form phrasal constituents and how phrasal constituents can combine to form larger constituents. Due to the creative capacity of language, it is clear that we do not simply learn lexically specific ways of putting words together -- there are regular, productive patterns of combination which apply to classes of words and phrases. By allowing for the mapping of words and phrases to general classes, the ontology supports the identification of such patterns of combination.
Why is such an ontology useful? It divides the linguistic domain up into types of entities to which each sentential constituent may correspond, thereby enabling the definition of broad constraints over the mapping between syntactic constituents and semantic entities. It further allows the definition of functions ranging over ontological entities, which indicate the ways in which entities can combine semantically. These functions are not fixed in advance by the ontology, but rather can be determined via linguistic analysis, in order to capture the range of relations expressible in language. The output of such functions is constrained to correspond to an entity in the ontology, thereby ensuring that there are at least very broad restrictions on what functions are possible. Thus the ontology reflects the types of entities which are expressible in language and guides the identification of coherent relations among these entities.
The definition of the ontology which Jackendoff uses stems in part
from psychological claims about the projection of entities in the real
world to a mental representation of those entities. Although the
cognitive processes of categorisation and so forth are possibly not of
direct concern to the computational lexical semanticist, the
linguistic motivations for a semantic ontology as introduced here and
the framework which such an ontology provides are reasons for adopting
one. There are in addition semantic reasons for the adoption of an
ontology, stemming from ``pragmatic anaphora'' (Hankamer and Sag
1976), in which anaphors like this and
that can refer to
entities of specific ontological categories compatible with the
linguistic context,
and psycholinguistic
and developmental studies (see Pinker 1989 for an
overview). Abstraction over cognitive structures is necessary to
account for children's ability to learn language. Furthermore, Talmy
talmy:83,talmy:88 has shown that most verb meanings
cross-linguistically are built around recurring elements of meaning
and their combinations. These studies strongly suggest that the
adoption of an ontology is necessary to capture generalisations about
language use.
The ontology as Jackendoff has proposed it, however, does not assume any explicit subdivision of the ontological categories, although he implicitly assumes a richer structure. These kinds of relations can easily be captured in a hierarchical ontology which has the conceptual categories introduced by Jackendoff at its top. This ontology would reflect categorisations of entities, events, etc. and relations between them. It therefore captures (a part of) world knowledge. Such an ontology is basic to constraint-based theories of grammar (e.g. HPSG) and have been widely used in computational approaches to natural language processing (see Copestake copestake:93b for an example). I will assume that an inheritance-based hierarchy is a critical representational component.
However, the lexical ontology which I will assume will be a linguistic ontology, following HPSG, as opposed to a world knowledge ontology, as emphasised in the introduction to this chapter. This means that information which is specifically relevant for the relationship between word forms and meanings will be represented here. For drink, for example, we must encode the information that the intransitive form of this verb has a specific default interpretation. That is, without more specific information ji31a means ji31b (Lascarides and Copestake lasc_copestake:97).
John drinks all the time. John drinks alcohol all the time.
This default interpretation cannot be explained solely on the basis of world knowledge since probabilistically drinking alcohol is not prima facie more likely than the drinking of other kinds of liquids. I will take advantage of the generalisations that can be made using an ontology, incorporating the notion of defaults which are associated with individual (groups of) lexical items.