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<Paper uid="P98-2187">
  <Title>A Generative Lexicon Perspective for Adjectival Modification</Title>
  <Section position="4" start_page="1143" end_page="1145" type="intro">
    <SectionTitle>
2 Conceptual versus Lexicographic
</SectionTitle>
    <Paragraph position="0"/>
    <Section position="1" start_page="1143" end_page="1143" type="sub_section">
      <SectionTitle>
Analysis of Lexical Items
</SectionTitle>
      <Paragraph position="0"> In this section, we outline the differences but also the cooperation between conceptual and lexicographic analysis of the semantics of lexical items to build a lexicon suitable for the development of generative devices.</Paragraph>
    </Section>
    <Section position="2" start_page="1143" end_page="1143" type="sub_section">
      <SectionTitle>
2.1 Adjectives in technical texts
</SectionTitle>
      <Paragraph position="0"> We have considered a sample of technical texts in French from various origins and used a simple tagging and extraction system developed for our needs.</Paragraph>
      <Paragraph position="1"> We have considered a total of 386 pages of text, with a total of 193 146 word occurences, among which, we have 14 598 occurences of adjectives. These occurences correspond to 754 different adjectives, among which 720 are restrictive adjectives. We will only consider this latter set.</Paragraph>
      <Paragraph position="2"> A small number of adjectives appear frequently: Fig. 1 Adjective frequencies interval nb. of adjectives concerned</Paragraph>
      <Paragraph position="4"> This means that 98 adjectives appear relatively frequently in texts, i.e. only about 13.6% of the total. In terms of occurences, these adjectives cover 11887 occurences, i.e. about 81% of the occurences.</Paragraph>
      <Paragraph position="5"> Adjectives from eight main 'semantic' families appear frequently. These families do not correspond exactly to those defined by (Dixon 91) (see also an introduction in (Raskin et al. 95)), which look too vague (figures have been rounded up or down to the closest integer): Fig. 2 Adjective semantic families Name example freq. (%) temporal actuel, pass6 10 evaluative bon, grand, cher 24 locational central, externe 10 aspectual courant, final 8 technical chimique 17 nationalities international 3 shapes rond, rectangulaire 4 society, culture economique, social 6 others 18 In terms of 'polysemic power', evaluative, locational, and shapes are the families which are the most polysemic, with a ratio of an average of 3.8 senses per adjective. Nationalities, technical and aspectual adjectives are much less polysemic.</Paragraph>
    </Section>
    <Section position="3" start_page="1143" end_page="1143" type="sub_section">
      <SectionTitle>
2.2 A conceptual analysis of adjectives
</SectionTitle>
      <Paragraph position="0"> The GL approach requires a conceptual analysis of adjectives in order to focus oil a relatively small number of senses. The idea is to isolate generic conceptual 'behaviors', while taking also into account the constraints on linguistic realizations as in the lexicographic approach.</Paragraph>
      <Paragraph position="1"> The principle that we attempt at validating is to define a 'deep' LCS representation for each predicative lexical item, which is generic enough to accomodate variations within a sense and precise enough to be meaningful and discriminatory w.r.t, other wordsenses. To be able to represent sense variations in an efficient and reliable way, the variable or underspecified elements should be 'low level' elements such as functions or paths. Semantic fields may also be altered, e.g. going from location to psychological or to epistemological (Pinker 93). Such an approach is being validated on various semantic families of verbs.</Paragraph>
      <Paragraph position="2"> The variable elements seem to belong to various ontologies (a crucial topic under intense investigation), such as the ontology of events (active, sleeping, terminated, etc.), of people's quilities, etc.</Paragraph>
    </Section>
    <Section position="4" start_page="1143" end_page="1144" type="sub_section">
      <SectionTitle>
2.3 Meanings of bon
</SectionTitle>
      <Paragraph position="0"> In this short document, for the purpose of illustration, let us consider the adjective bon (corresponding quite well to good), which is one of the most polysemic adjective: 25 senses identified in WordNet (e.g. (Fellbaum 93)). In fact, bon can be combined with almost any noun in French, and as (Katz 66) pointed out, 9ood would need as many different readdeg ings as there are functions for objects.</Paragraph>
      <Paragraph position="1"> We have identified the following senses and sense variations (metaphors and metonymies in particular, expressed as in (Lakoff 80)): 1. Idea of a good working of a concrete object w.r.t, what it has been designed for: un bon tournevis, de bons yeux (good screw-driver, good  eyes). Metaphors abound: e.g.: 'communication acts as tools': une bonne plaisanterie/mise au point (a good joke), 'function for tool' (un boa odorat), 'paths as tools' ( a good road). 1 Metonymies are rather unusual since if X is a part of Y, a good X does not entail a good Y 2  2. Positive evaluation of moral, psychological,  physical or intellectual qualities in humans: bonne personne, boa musician, (good persoa, good musician). The basic sense concerns professions and related activites or humans as a whole: it is the ability of someone to realize something for professions, and, for humans, the high level of their moral qualities (an enumeration call be given or a kind of higher-order, typed expression). null This second sense could be viewed as a large metaphor of the first, with a structure-preserving transposition to a different ontology: from tools to professional or moral skills.</Paragraph>
      <Paragraph position="2"> There are some 'light' metaphors such as: 'social positions or ranks as professions' (a good boss/father/friend / citizen), and a large number of metonymies: 'image for person, image being a part of a person' (a good reputation), 'tool for profession' (a good scalpel), 'place for profession' ( a good restaurant). These metaphors have a good degree of systematicity.</Paragraph>
      <Paragraph position="3"> 3. Intensifier of one or more properties of the noun, producing an idea of pleasure and satisfaction (this is different for sense 5) 3: noun(+edible): good meal/dish/taste = tasty, with metonymies such as 'container tbr containee' ( a good bottle/glass), noun(+fine-art): good film/book/painting = valuable, with metonymies such as 'physical support for contents' (good CD), noun(+smelling): good odor, noun(+psycho): good relation/experience noun(+human relations): good neighbours.</Paragraph>
      <Paragraph position="4"> Note that bon can only be used with neutral or positive nouns, we indeed do not have in French *good ennemies, *good humidity with the sense outlined here.</Paragraph>
      <Paragraph position="5"> 4. Quantification applied to measures or to quantities: o good meter, a good liter, o good lIn the combination noun + adjective,&amp;quot; the norm is the element that undergo the metaphor. The adjective being a predicate, it is its relation to the noun it modifies which is metaphorical, similarly to the relation verb-noun. The semantics of the noun remains a priori unaltered. 2This needs refinements: there are some weak forms of upward inheritance in the part-of relation: e.g. if the body of a car is red, then the car is said to be red.</Paragraph>
      <Paragraph position="6"> 3Norms are being defined for about 600 top-most nodes of a general purpose ontology in different projects and research groups (e.g. NMSU, ISI, Eagles EEC project), they will be used as soon as available.</Paragraph>
      <Paragraph position="7"> amount/salary, a good wind. In this case, good means a slightly more than the unit/measure indicated or above the average (for terms which are not measure units such as wind or salary).</Paragraph>
      <Paragraph position="8"> This sense being quite different since it is basically a quantifier, it won't be studied hereafter. 5. Idea of exactness, accuracy, correctness, validity, freshness, etc.: un bon raisonnement/calcul = exact, accurate (a good deduction/computation), good note~ticket = valid, a good meat = fresh or eatable, a good use = appropriate, good knowledge = efficient, large and of good quality. The meaning of bon is therefore underdetermined. Depending on the noun, the semantics of bon is slightly different, this is not really a case of co-composition. It is the semantic type of the noun and that of the selected predicate in the telic role of the noun which determine the meaning of the adjective in this particular NP. We call this phenomenon, by comparison with selective binding, selective projection, because the meaning is projected from the noun's telic role. Sense 5 is substantially different from sense 1: it is basically boolean (e.g. exact or not), there is no idea of tool, function or even activity.</Paragraph>
      <Paragraph position="9"> Bon appears in a large number of fixed or semi-fixed forms such as: le boa godt, le bon sans, le boa temps, une bonne giffle.</Paragraph>
      <Paragraph position="10"> Almost the same behavior is observed for all evaluative adjectives such as excellent, terrific, bad or lousy in French. For example, for mauvais (bad), senses 1, 2 and 3 are identical, sense 4 is only applicable to amounts (mauvais salaire), not to units and sense 5 is almost identical, it conveys the idea of erroneous deduction, invalid ticket, bad use and rotting meat. Note that in WordNet, bad has only 14 senses, whereas good has 25 senses, with no clear justification.</Paragraph>
    </Section>
    <Section position="5" start_page="1144" end_page="1145" type="sub_section">
      <SectionTitle>
2.4 A comparison with WordNet
</SectionTitle>
      <Paragraph position="0"> We have carried out a comparison of our conceptual analysis with the lexicographic analysis in ~VordNet.</Paragraph>
      <Paragraph position="1"> We have compared manually a subset of 54 adjectives among the above mentioned frequently used adjectives. Among these adjectives, 30 are polysenfic in our approach while 44 belong to several synsets in WordNet:  largely (for highly polysemic adjectives), for which our approach identifies much less senses.</Paragraph>
    </Section>
    <Section position="6" start_page="1145" end_page="1145" type="sub_section">
      <SectionTitle>
2.5 Underspecificatlon versus polysemy
</SectionTitle>
      <Paragraph position="0"> Each of the senses of bon has many facets and interpretations depending on the noun it modifies. As for verbs or nouns (Busa 97), polymorphic types are used to represent the semantics of the expected nouns, viewed as arguments of the adjective predicate. The semantic representation associated with a sense is therefore underspecified and tuned to reflect this polymorphism. The scope of underspecified elements must however be bounded and precisely defined by 'lexical' types and by additional constraints. The generative expansion of underspecified fields can be defined from lexical items using a fix-point semantics approach (Saint-Dizier 96).</Paragraph>
      <Paragraph position="1"> 2.6 Towards an automatic acquisition of conceptual descriptions Some on-line resources and dictionaries may efficiently contribute to this task. We have considered several mono- and bi-lingual dictionaries in order to evaluate convergences. Only those structured on a conceptual basis are worth considering.</Paragraph>
      <Paragraph position="2"> Among them, the Harrap's German-French dictionary is very nicely structured in a conceptual perspective, providing translations on an accurate semantic basis. Senses are slightly more expanded than in the GL approach to account for translation variations, but closely related senses can be grouped to form the senses defined above.</Paragraph>
      <Paragraph position="3"> Another source of knowledge for English is Corelex 4 which is just being made accessible. It contains word definitions specifically designed for the GL. Its evaluation is about to start.</Paragraph>
    </Section>
  </Section>
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