Unni Cathrine Eiken February 2005

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(4- 7) bistå,etterforsker,lensmann bistå,etterforsker,politi ha,etterforsker,observasjon kontakte,etterforsker,vitne mene,etterforsker,? rigge,etterforsker,lyskaster undersøke,etterforsker,åsted assist, investigator, deputy assist, investigator, police have, investigator, observation contact, investigator, witness mean, investigator, ? build-up, investigator,searchlight examine, investigator, crime scene For each of the predicates in (4-7), we want to find the other arguments, in addition to etterforsker (investigator), which occur in the corpus material as the first argument of the predicate. Traversing the EPAS list in search of these nominal arguments yields the list presented in (4-8). Pronouns and empty argument slots are omitted from the association since they generally occur in too many different context patterns to contribute with relevant information in this kind of analysis. (4- 8) ha,politi,medarbeider ha,politi,teori kontakte,politi,vitne mene,politi,? undersøke,politi,aktivitet have,police,co-worker have,police,theory contact,police,witness mean,police,? examine,police,activity As can be seen from the EPAS in (4-8), politi (police) is the only other argument which occurs in the same contexts as etterforsker (investigator). So far, the association tells us that there is a relationship between the concepts etterforsker (investigator) and politi (police) in the sense that these words occur in the same environments in the text collection. Level 2 In order to explore the possibility of further associated concepts, the association method goes one level further. Basically, the first step of the association is repeated, but with new parameters; for each of the first arguments in (4-8) we need to know which other words can occur in the same contextual position. Therefore the EPAS list is again consulted and all the other first arguments that occur in the same environment as politi (police) are returned. This produces the list in (4-9). 70
(4- 9) avklare,obduksjon,? bede-om,lensmann,assistanse bede-om,Fonn, bede-om,lensmann, bekrefte,lensmann,? bekrefte,politimester,? finne,leteaksjon,kvinne få,kjæreste,telefon gi,Fonn,opplysning gi,kamera,indikasjon gi,lensmann,opplysning gi,lensmann,opplysning gi,vitneavhør,indikasjon ha,etterforsker,observasjon kjenne,generic-nom,Slåtten kontakte,etterforsker,vitne mene,etterforsker,? tro,lensmann,? clarify,autopsy,? ask-for,sergeant,assistance ask-for,Fonn,? ask-for,sergeant,? confirm,sergeant,? confirm,chief of police,? find,search party,woman get,boy/girlfriend,telephone give,Fonn,information give,camera,indication give,sergeant,information give,sergeant,information give,interview,indication have,investigator,observation know,generic-nom,Slåtten contact,investigator,witness mean,investigator,? believe,sergeant,? As a step toward disregarding arguments which do not occur often enough in the context in question to be of significance, the method may be limited to only considering arguments which occur more than once in the text material. In the case of a larger text collection, a different method of sorting out low frequent arguments would have to be adopted; for the small data set in this project, disregarding arguments which only occur once was of use. The steps as outlined above produces the following associated group of concepts: Figure 6 etterforsker (investigator) politi (police) lensmann (sergeant) Fonn (Fonn) 71
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University of Bergen Section for li
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Preface The project presented in th
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Table of Contents 1 INTRODUCTION AN
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1 Introduction and problem statemen
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patterns found in a text collection
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The results obtained in this projec
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The term anaphor describes a lingui
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2.1.1.1 Discourse representation th
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eferring to BT. The NP which is lin
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esolution system will not be able t
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(2- 12) REC SUBJ EXIST OBJ IND-OBJ
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Figure 1 17
Page 25 and 26: means that the algorithm would prop
Page 27 and 28: for an overview). Many of these sys
Page 29 and 30: (2- 15) a. Politiet etterlyste i da
Page 31 and 32: section. The theory dates back to t
Page 33 and 34: 2.2.2 Different types of context So
Page 35 and 36: neighbours. For example, a target w
Page 37 and 38: with it. Selectional constraints al
Page 39 and 40: 3 From text to EPAS - the extractio
Page 41 and 42: 3.2 Predicate-argument structures "
Page 43 and 44: speaker flexibility with regards to
Page 45 and 46: and woman occur together both in su
Page 47 and 48: occur with. Arguments which are unl
Page 49 and 50: 3.3.1 NorGram in outline Norsk komp
Page 51 and 52: Figure 3 The most useful structure
Page 53 and 54: 3.4 Altering the source As already
Page 55 and 56: (3- 12) (3- 13) Politiet leter ette
Page 57 and 58: ARG1 and ARG2 arrays display a valu
Page 59 and 60: (3- 20) Anne Slåtten bodde i et st
Page 61 and 62: value and highly desirable. As such
Page 63 and 64: this project, this can be interpret
Page 65 and 66: The process of classifying the cons
Page 67 and 68: There are several different distanc
Page 69 and 70: . ankomme,etterforsker,?,? ankomme,
Page 71 and 72: Test 2 Training set: EPAS_arg1 with
Page 73 and 74: The training and test material was
Page 75: • level 0: words which co-occur w
Page 79 and 80: (4-10) below shows the output for t
Page 81 and 82: In the introduction to this chapter
Page 83 and 84: the EPAS can be used in the classif
Page 85 and 86: exemption of jobbe-utfra, none of t
Page 87 and 88: antecedent for (4-15a). In the case
Page 89 and 90: Figure 7 Interestingly enough, howe
Page 91 and 92: When testing on knowledge-dependent
Page 93 and 94: Firth, J. R. (1957): A synopsis of
Page 95 and 96: Appendix A: Ekstraktor.pl - algorit
Page 97 and 98: finnARG2(); This function has exact
Page 99 and 100: #legger lest linje inn i @prt derso
Page 101 and 102: sub fjernEP{ #fjerner elementer fra
Page 103 and 104: } splice(@ARGx); $imax = @ARG3ep; @
Page 105 and 106: } else{ } } } push(@liste, $ARG0ep[
Page 107 and 108: 101 Appendix C: the EPAS list 23-å
Page 109 and 110: 103 obdusere,,kvinne observere,,23-
Page 111 and 112: Appendix D: Text aligned with EPAS
Page 113 and 114: eventualiteter. Vi varslet Kripos.
Page 115 and 116: Etterforskerne har flere observasjo
Page 117 and 118: # Subrutine som tar inn argumentnum
Page 119 and 120: Appendix F: POS-based structures SE
Page 121: Vi har ingen spesiell teori som vi
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Unni Cathrine Eiken February 2005

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