| { | |
| "paper_id": "C80-1033", | |
| "header": { | |
| "generated_with": "S2ORC 1.0.0", | |
| "date_generated": "2023-01-19T13:05:28.770264Z" | |
| }, | |
| "title": "CONNOTATION AS A FORM OF I ~qFERENC E", | |
| "authors": [ | |
| { | |
| "first": "J", | |
| "middle": [ | |
| "B" | |
| ], | |
| "last": "Berthelin", | |
| "suffix": "", | |
| "affiliation": { | |
| "laboratory": "", | |
| "institution": "University of Essex (language and linguistics)", | |
| "location": { | |
| "addrLine": "Wivenhoe Pk" | |
| } | |
| }, | |
| "email": "" | |
| } | |
| ], | |
| "year": "", | |
| "venue": null, | |
| "identifiers": {}, | |
| "abstract": "Story-processing systems have to deal, or avoid dealing, with INFERENCE CONTROL ''6' Ii, 13. when designing one such system 2, we were greatly helped by the \"(ERC)RC\" expression for connotation I. Our system is specialised in multifaceted descriptions of characters (not, however, in the most difficult problems of beliefs about beliefs 4 and 8): here we present another aspect of the story character processing, namely the recursive EXPLANATION of inconsistencies appearing in the description of a character. We give a very schematic system overview, then some details about the CONNOTATION rules and an example of their application to a story. posed to (\"fromage\" RC(\"cheese\")) RC(\"french\"), but also situation-specific ones, as (\"cheese\" RC(\"cheese as geological stuff\") RC(\"bizarre\"), in the processing of a robot who asked what the moon is made of. As Barthes then remarks, connotations may be based on a set of initial expressions rather than on a single one, which is expressed by (EiRCl, E2RC 2 ..... EnRCn) R C This seems to be an essential feature of connotations, since it allows emphasis on 'connoted' contents by means of an accumulation of signifiers. Another feature, elegantly illustrated in 'l'envers des signes 'i0 by the two steps ((\"voile\" RC(\"navire\"))RC(\"po~sie\"))RC(\"rh~torique\"), is their recursivity.", | |
| "pdf_parse": { | |
| "paper_id": "C80-1033", | |
| "_pdf_hash": "", | |
| "abstract": [ | |
| { | |
| "text": "Story-processing systems have to deal, or avoid dealing, with INFERENCE CONTROL ''6' Ii, 13. when designing one such system 2, we were greatly helped by the \"(ERC)RC\" expression for connotation I. Our system is specialised in multifaceted descriptions of characters (not, however, in the most difficult problems of beliefs about beliefs 4 and 8): here we present another aspect of the story character processing, namely the recursive EXPLANATION of inconsistencies appearing in the description of a character. We give a very schematic system overview, then some details about the CONNOTATION rules and an example of their application to a story. posed to (\"fromage\" RC(\"cheese\")) RC(\"french\"), but also situation-specific ones, as (\"cheese\" RC(\"cheese as geological stuff\") RC(\"bizarre\"), in the processing of a robot who asked what the moon is made of. As Barthes then remarks, connotations may be based on a set of initial expressions rather than on a single one, which is expressed by (EiRCl, E2RC 2 ..... EnRCn) R C This seems to be an essential feature of connotations, since it allows emphasis on 'connoted' contents by means of an accumulation of signifiers. Another feature, elegantly illustrated in 'l'envers des signes 'i0 by the two steps ((\"voile\" RC(\"navire\"))RC(\"po~sie\"))RC(\"rh~torique\"), is their recursivity.", | |
| "cite_spans": [], | |
| "ref_spans": [], | |
| "eq_spans": [], | |
| "section": "Abstract", | |
| "sec_num": null | |
| } | |
| ], | |
| "body_text": [ | |
| { | |
| "text": "The allusiveness of human languages, in addition to being quite convenient in social life, justifies the use of variable amounts of i n t e 1 -1 i g e n c e in processing a sentencer according to the number of reasoning steps leading to a position where a satisfactory reaction be-,14 comes possible, like \"to redefine 'substance when reading Spinoza\". Let us represent a first step by \"ERC\" i.e. \"an expression is related to a content ''1, which Barthes calls the denotation: the second reasoning step will be represented in the connotation formula: \" (ERC) RC\".", | |
| "cite_spans": [], | |
| "ref_spans": [], | |
| "eq_spans": [], | |
| "section": "Introduction", | |
| "sec_num": null | |
| }, | |
| { | |
| "text": "It does not determine exactly where the reasoning step leads to: if we write E's content as C(E), we may have quite general connotations like (\"cheese\"RC(\"cheese\"))RC(\"english\") as op-As a beginning we made an attempt to express this in AI terms by writing a program, BAQUIL, which finds the connotations with structure(E I RCi, E2RC2)RC in a recursive way. The interest of such connotations can be shown by15:", | |
| "cite_spans": [], | |
| "ref_spans": [], | |
| "eq_spans": [], | |
| "section": "Introduction", | |
| "sec_num": null | |
| }, | |
| { | |
| "text": ".a doctor asks:\"how is he feeling ?\"", | |
| "cite_spans": [], | |
| "ref_spans": [], | |
| "eq_spans": [], | |
| "section": "Introduction", | |
| "sec_num": null | |
| }, | |
| { | |
| "text": ".the nurse answers:\"he is groaning.\"", | |
| "cite_spans": [], | |
| "ref_spans": [], | |
| "eq_spans": [], | |
| "section": "Introduction", | |
| "sec_num": null | |
| }, | |
| { | |
| "text": "where the nurse means, by connotation,that the patient is suffering: (\"groaning\" RC(\"groaning\") RC(\"suffering)), but our understanding is directed by the previous interrogation, so that the definitive result we expect from our system will be (\"feeling\"RC(\"feeling\"), \"groaning\"RC(\"groaning\") )RC(\"suffering\"). This result shall be reached by consulting a semantic network and observing that 'groaning' is not exactly a case of 'feeling', but an expression of it. Thus \" the nurse means he is suffering\" is both a connotation and an inference, and seemingly a useful one: compare with Charniak's 6 \"demon-demon in- in terms of the 'notations' themselves.", | |
| "cite_spans": [], | |
| "ref_spans": [], | |
| "eq_spans": [], | |
| "section": "Introduction", | |
| "sec_num": null | |
| }, | |
| { | |
| "text": "M3 means \"use the lexical taxonomy when trying to recognize a situation\"; as a result it introduce a distinction between natural languages, for the subcategories of (for instance) \"inconsistency\" are not the same in different dictionariesl Consider French and English, \"error\"", | |
| "cite_spans": [], | |
| "ref_spans": [], | |
| "eq_spans": [], | |
| "section": "Introduction", | |
| "sec_num": null | |
| }, | |
| { | |
| "text": "and \"mistake\" vs. \"erreur\" and \"m@rise\", or worse: the two cases of \"to tell a lie\" in Russian, i.e. \"vrat'\" vs. \"l'gat'\". RULES APPLIED: C4 \"lexical necessity\"", | |
| "cite_spans": [], | |
| "ref_spans": [], | |
| "eq_spans": [], | |
| "section": "Introduction", | |
| "sec_num": null | |
| }, | |
| { | |
| "text": "R3 \"topic\"", | |
| "cite_spans": [], | |
| "ref_spans": [], | |
| "eq_spans": [], | |
| "section": "Introduction", | |
| "sec_num": null | |
| }, | |
| { | |
| "text": "R6 if a character's discourse matches an inference, BAQUIL checks whether the character is clever or has made a lucky guess etc.", | |
| "cite_spans": [], | |
| "ref_spans": [], | |
| "eq_spans": [], | |
| "section": "Introduction", | |
| "sec_num": null | |
| }, | |
| { | |
| "text": "C3 \"lexical exclusion\"", | |
| "cite_spans": [], | |
| "ref_spans": [], | |
| "eq_spans": [], | |
| "section": "R5 \"tendency\"", | |
| "sec_num": null | |
| }, | |
| { | |
| "text": "R71if the story-telling contradicts an inferen-and~ce, the inference is 'discarded'; if the R8Ydiscarded inference is matched by a discourse, one looks for an 'error' or 'trick' etc.", | |
| "cite_spans": [], | |
| "ref_spans": [], | |
| "eq_spans": [], | |
| "section": "R5 \"tendency\"", | |
| "sec_num": null | |
| }, | |
| { | |
| "text": "While not achieving much by itself, Baquil is 2 an important component of the larger system currently built at Paris 6, and could probably also be integrated in a large AI MT system as an expert of indirect descriptions of characters, for instance it could recognize the use of a nationality adjective suggesting a character trait (Cretan for liar, etc.), which is helpful in many cases: when the nationality adjective is not familiar in the target language (Chines texts about the ancient kingdoms), but also when there are several possible interpretations for the nationality adjective in terms of personality ( 'qua' ambiguity).", | |
| "cite_spans": [], | |
| "ref_spans": [], | |
| "eq_spans": [], | |
| "section": "Conclusion", | |
| "sec_num": null | |
| } | |
| ], | |
| "back_matter": [], | |
| "bib_entries": { | |
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| "BIBREF15": { | |
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| "title": "The story in the sample session is adapted from", | |
| "authors": [], | |
| "year": 1979, | |
| "venue": "The Big Red Joke Book\" by Benton and Loomes", | |
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| "raw_text": "The story in the sample session is adapted from \"The Big Red Joke Book\" by Benton and Loomes, Pluto Press, London, 1979.", | |
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| } | |
| }, | |
| "ref_entries": { | |
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| "text": "explanation of how the system runs i) the dictionary input procedure builds, from a file whose structure is shown in the ' sample session ', a classical semantic network 7'9\"'' 2) the story specialist submits sentences to aparser 12 and the resulting case structures to the story character specialist, whose actions include the c o m p a r i s o n s and i n f e r e n c e s detailed here. 3) output procedures express the inferences in English and, on request, detail the representation of each character in the story. Metarules of BAQUIL (this page and the following three will develop what rules are applied by the story character specialist: this includes METARULES, RULES OF COMPARISON and INFERENCE RULES.) MI BAQUIL starts a connotation or inference only when a comparison rule has been applied to a pair of predicates which are related to the set of descriptors of one character: the predicates are versions of the semantic case structure in terms of the current character description, and are called 'NOTATIONS' M2 Except when specified otherwise (inference rules R6, R7), the inference is expressed by a 'notation' whose verb is a subcategory of either CHANGE or INCONSISTENCY. consistency. The metarules are represented in BA-QUIL by instructions: Mi in the NOTATION procedure, M2 and M3 in the CONNOTATION procedure. The latter also contain the instruction corresponding to the inference rules, while the comparison rules form the comparison procedure. Discussion of the metarules M1expresses the hypothesis that many interesting antinomies can be detected during the pairwise matching of predicates concerning one story character.\" M2 aims to expres a more or less syntactic finding about the description of a character (co-presence of two antinomic 'notations')", | |
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