Base_JSON/prefixI/json/isa/2021.isa-1.3.json

{
    "paper_id": "2021",
    "header": {
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        "date_generated": "2023-01-19T07:12:24.589722Z"
    },
    "title": "Annotating Quantified Phenomena in Complex Sentence Structures Using the Example of Generalising Statements in Literary Texts",
    "authors": [
        {
            "first": "Tillmann",
            "middle": [],
            "last": "D\u00f6nicke",
            "suffix": "",
            "affiliation": {
                "laboratory": "",
                "institution": "University of G\u00f6ttingen",
                "location": {}
            },
            "email": "tillmann.doenicke@uni-goettingen.de"
        },
        {
            "first": "Luisa",
            "middle": [],
            "last": "G\u00f6deke",
            "suffix": "",
            "affiliation": {
                "laboratory": "",
                "institution": "University of G\u00f6ttingen",
                "location": {}
            },
            "email": "luisa.goedeke@uni-goettingen.de"
        },
        {
            "first": "Hanna",
            "middle": [],
            "last": "Varachkina",
            "suffix": "",
            "affiliation": {
                "laboratory": "",
                "institution": "University of G\u00f6ttingen",
                "location": {}
            },
            "email": "hanna.varachkina@stud.uni-goettingen.de"
        }
    ],
    "year": "",
    "venue": null,
    "identifiers": {},
    "abstract": "We present a tagset for the annotation of quantification which we currently use to annotate certain quantified statements in fictional works of literature. Literary texts feature a rich variety in expressing quantification, including a broad range of lexemes to express quantifiers and complex sentence structures to express the restrictor and the nuclear scope of a quantification. Our tagset consists of seven tags and covers all types of quantification that occur in natural language, including vague quantification and generic quantification. In the second part of the paper, we introduce our German corpus with annotations of generalising statements, which form a proper subset of quantified statements.",
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        "abstract": [
            {
                "text": "We present a tagset for the annotation of quantification which we currently use to annotate certain quantified statements in fictional works of literature. Literary texts feature a rich variety in expressing quantification, including a broad range of lexemes to express quantifiers and complex sentence structures to express the restrictor and the nuclear scope of a quantification. Our tagset consists of seven tags and covers all types of quantification that occur in natural language, including vague quantification and generic quantification. In the second part of the paper, we introduce our German corpus with annotations of generalising statements, which form a proper subset of quantified statements.",
                "cite_spans": [],
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                "section": "Abstract",
                "sec_num": null
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        "body_text": [
            {
                "text": "Quantification is a core element of human language because it allows us to make statements about groups or classes of entities, in contrast to statements about individually referenced entities.",
                "cite_spans": [],
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                "section": "Introduction",
                "sec_num": "1"
            },
            {
                "text": "One subtype of quantified statements are generalising or generic (for now summarised as generalising) statements that involve quantification over assumed members of a class rather than contextually given entities. These generalising statements are particularly interesting for NLP applications that operate on discourse-level, e.g. in knowledge extraction (e.g. Bhakthavatsalam et al., 2020) and argumentation mining (e.g. Becker et al., 2016) . But also in computational literary studies, generalising statements can be viewed as indicators (i.e. features) for meta-level phenomena such as passages of (self-)reflection (cf. Lahn and Meister, 2016, p. 184) or passages addressing real-world issues within a fictional text (e.g. Vesper, 2014) .",
                "cite_spans": [
                    {
                        "start": 362,
                        "end": 391,
                        "text": "Bhakthavatsalam et al., 2020)",
                        "ref_id": "BIBREF3"
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                    {
                        "start": 423,
                        "end": 443,
                        "text": "Becker et al., 2016)",
                        "ref_id": "BIBREF2"
                    },
                    {
                        "start": 626,
                        "end": 657,
                        "text": "Lahn and Meister, 2016, p. 184)",
                        "ref_id": null
                    },
                    {
                        "start": 729,
                        "end": 742,
                        "text": "Vesper, 2014)",
                        "ref_id": "BIBREF48"
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                "section": "Introduction",
                "sec_num": "1"
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                "text": "Put very concisely, one traditionally differentiates between (determiner or generic) quantification on NP-level and (adverbial or generic) quantification on clause-level (Krifka and Gerstner, 1987; Partee, 1990; Krifka, 2016) , which is also reflected in certain annotation schemes (cf. Friedrich et al., 2015) . However, for such higher-level applications, where the presence of quantification or, more specifically, generalisation serves as a feature, the syntactic or semantic structure of quantified statements plays only a subordinate role. Therefore, performing a syntactic and/or semantic analysis during the annotation would be laborious but not expedient-especially in domains where sentences tend to employ a complex syntactic structure, such as literary texts. Moreover, quantified statements are not always marked by an overt linguistic marker but can also be covertly quantified in the case of generic statements.",
                "cite_spans": [
                    {
                        "start": 170,
                        "end": 197,
                        "text": "(Krifka and Gerstner, 1987;",
                        "ref_id": "BIBREF34"
                    },
                    {
                        "start": 198,
                        "end": 211,
                        "text": "Partee, 1990;",
                        "ref_id": "BIBREF45"
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                    {
                        "start": 212,
                        "end": 225,
                        "text": "Krifka, 2016)",
                        "ref_id": "BIBREF33"
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                    {
                        "start": 287,
                        "end": 310,
                        "text": "Friedrich et al., 2015)",
                        "ref_id": "BIBREF19"
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                ],
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                "section": "Introduction",
                "sec_num": "1"
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                "text": "For generalisation specifically, previous work commonly differentiates between generalisation over (kinds of) individuals and generalisation over recurring events/situations (Krifka et al., 1995; Carlson, 2011; Friedrich and Palmer, 2014) . Similar to the syntactic categorisation, this is not only an insufficient differentiation if one is interested in generalising statements as a whole; it further constitutes a limitation, since it is possible to quantify (and thus generalise) over other types of entities than the two just mentioned. We shall expand on the theoretical syntactic and semantic considerations in Section 2 and give an overview of related practical challenges in literary texts in Section 3.",
                "cite_spans": [
                    {
                        "start": 174,
                        "end": 195,
                        "text": "(Krifka et al., 1995;",
                        "ref_id": "BIBREF35"
                    },
                    {
                        "start": 196,
                        "end": 210,
                        "text": "Carlson, 2011;",
                        "ref_id": "BIBREF7"
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                        "start": 211,
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                        "text": "Friedrich and Palmer, 2014)",
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                "section": "Introduction",
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                "text": "Considering both the theoretical and practical aspects, we developed a tagset and annotation guidelines for generalising statements that are neither bound to syntactic nor to semantic properties and preserve only the information which is most important in our view: the type of quantification (universal/existential/vague etc.). This shallow annotation scheme allows a comparatively fast annotation of generalising statements, which is especially valu- Nuclear scope  determiner, subordinate clause, main clause,  adverb,  if-clause,  assertion,  negation, common NP, predication, generic topic focus Table 1 : Examples for tripartite-structure components (Partee, 1990, p. 10) able in the literary domain. Since our annotation scheme can be used for quantified statements in general, we will present it as such in Section 4 and turn to generalising statements in Section 5. Afterwards, Section 6 presents details about our corpus and annotation process. Sections 7 and 8 discuss related and future work, respectively.",
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                        "start": 656,
                        "end": 677,
                        "text": "(Partee, 1990, p. 10)",
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                "ref_spans": [
                    {
                        "start": 453,
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                        "text": "Nuclear scope  determiner, subordinate clause, main clause,  adverb,  if-clause,  assertion,  negation,",
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                        "text": "Table 1",
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                "section": "Introduction",
                "sec_num": "1"
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                "text": "In English (and in German), quantificational notions are typically triggered by determiners, e.g. all, most etc., or adverbs, e.g. always, usually etc. Following Lewis (1975) , Kamp (1981) and Heim (1982) , we assume quantified statements to consist of a tripartite logical form consisting of the quantifier Q, the restrictor and the nuclear scope:",
                "cite_spans": [
                    {
                        "start": 162,
                        "end": 174,
                        "text": "Lewis (1975)",
                        "ref_id": "BIBREF39"
                    },
                    {
                        "start": 177,
                        "end": 188,
                        "text": "Kamp (1981)",
                        "ref_id": "BIBREF30"
                    },
                    {
                        "start": 193,
                        "end": 204,
                        "text": "Heim (1982)",
                        "ref_id": "BIBREF25"
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                ],
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                "section": "Quantification",
                "sec_num": "2"
            },
            {
                "text": "(1) Q[x :",
                "cite_spans": [],
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                "eq_spans": [],
                "section": "Quantification",
                "sec_num": "2"
            },
            {
                "text": "restr(x)][scope(x)]",
                "cite_spans": [],
                "ref_spans": [],
                "eq_spans": [],
                "section": "Quantification",
                "sec_num": "2"
            },
            {
                "text": "We subsume determiners and adverbs to both function as quantifiers in this model:",
                "cite_spans": [],
                "ref_spans": [],
                "eq_spans": [],
                "section": "Quantification",
                "sec_num": "2"
            },
            {
                "text": "(2) a. Most horses have four legs.",
                "cite_spans": [],
                "ref_spans": [],
                "eq_spans": [],
                "section": "Quantification",
                "sec_num": "2"
            },
            {
                "text": "b. MOST[x : horse(x)][four-legged(x)]",
                "cite_spans": [],
                "ref_spans": [],
                "eq_spans": [],
                "section": "Quantification",
                "sec_num": "2"
            },
            {
                "text": "(3) a. Usually, a horse has four legs.",
                "cite_spans": [],
                "ref_spans": [],
                "eq_spans": [],
                "section": "Quantification",
                "sec_num": "2"
            },
            {
                "text": "b. USUALLY[x : horse(x)][four-legged(x)]",
                "cite_spans": [],
                "ref_spans": [],
                "eq_spans": [],
                "section": "Quantification",
                "sec_num": "2"
            },
            {
                "text": "This approach enables us to include various clause-level forms of quantification into a unifying analysis. The forms can differ in syntactic realisation; Table 1 shows some examples for how quantifier, restrictor and nuclear scope can be realised in natural language, beyond determiners/adverbs and common noun phrases.",
                "cite_spans": [],
                "ref_spans": [
                    {
                        "start": 154,
                        "end": 161,
                        "text": "Table 1",
                        "ref_id": null
                    }
                ],
                "eq_spans": [],
                "section": "Quantification",
                "sec_num": "2"
            },
            {
                "text": "In addition to the syntactic diversity of quantification, it can range over all types of semantic entities. While quantification over individuals, as in (2) and (3), and events/situations, so-called habituals (e.g. Rimell, 2004) as in (4), may be most notable, it is also possible to quantify over e.g. times, as in (5), and locations, as in (6). 3 Challenges in Literary Texts",
                "cite_spans": [
                    {
                        "start": 215,
                        "end": 228,
                        "text": "Rimell, 2004)",
                        "ref_id": "BIBREF47"
                    }
                ],
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                "section": "Quantification",
                "sec_num": "2"
            },
            {
                "text": "We are interested in the distribution of such structures as \"general statements\" or \"statements of universal validity\" in German fictional texts. Therefore, we are aiming at annotating quantified statements in any form they may occur in. Our corpus consists of fictional texts written or published between 1650 and 1950. Hence, we are not only confronted with complex sentence structures, which are typical for literary texts, but also with older versions of German. We need an annotation concept that lets us capture quantified expressions in all their variety. Although our research does not primarily focus on the surface quantification, but on the generalising function that these structures fulfil, our work has a solid foundation in (formal) linguistics, as we will show in Section 4. Therefore, the transfer of theoretical knowledge about quantification into computational linguistics turns out to be a challenge-especially for analysing the literary domain. Particularly, we are facing three main challenges: First, the default formal analysis of quantification by defining quantifier, restrictor, and scope (as established in the previous section) can be highly complex in sentences of fictional writing. On top of that, German allows comparatively long and complex multi-clause sentences, especially in older language variants. This issue is illustrated in (7), where we already cut out several embedded if-clauses (German: wenn 'if') out of this one sentence. The English translation in (7') does not take the various if-clauses on and splits them up into separate sentences: If-clauses, as in (7) can be considered as restrictors (compare Table 1 ); and the then-clause (German: so 'then') can be considered as nuclear scope. Our first problem manifests itself here: The if-clauses form a list of coordinated restrictors for only one scope, and it remains unclear how many individual quantified statements there are or whether the individual restrictors are meant to be joined by logical conjunction or disjunction. Resolving such issues would require a laborious and-in our caseredundant analysis. For ease of presentation, we shall only use English examples in the following, taken from official translations. The original examples are provided in the appendix (B).",
                "cite_spans": [],
                "ref_spans": [
                    {
                        "start": 1651,
                        "end": 1658,
                        "text": "Table 1",
                        "ref_id": null
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                ],
                "eq_spans": [],
                "section": "Quantification",
                "sec_num": "2"
            },
            {
                "text": "Second, we have to deal with ambivalent syntactic structures, leading to scope ambiguity. If a sentence carries more than one quantifier, different readings arise due to the dominant quantification.",
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                "text": "(8) Help upon the spot is the thing you often most want in the country. (Goethe, EA, p. 49) In (8) we find two generic expressions (help upon the spot and the country) combined with the adverbial often. Third, the absence of overt markers Tag Description ALL overt universal quantification MEIST overt majority quantification EXIST overt existential quantification ZAHL overt numerical quantification DIV overt vague quantification BARE none of the above + covert quantification NEG any of the above + negation for quantification is a greater problem than an overpresence. The generic NPs (cf. Leslie and Lerner, 2016) , e.g. business and life in (9), certainly have a generalising function in this context, but are not overtly quantified.",
                "cite_spans": [
                    {
                        "start": 72,
                        "end": 80,
                        "text": "(Goethe,",
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                    },
                    {
                        "start": 81,
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                        "text": "EA,",
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                    {
                        "start": 85,
                        "end": 91,
                        "text": "p. 49)",
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                    {
                        "start": 594,
                        "end": 618,
                        "text": "Leslie and Lerner, 2016)",
                        "ref_id": "BIBREF38"
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                ],
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                "sec_num": "2"
            },
            {
                "text": "(9) Business requires earnestness and method;",
                "cite_spans": [],
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                "eq_spans": [],
                "section": "Quantification",
                "sec_num": "2"
            },
            {
                "text": "life must have a freer handling. (Goethe, EA, p. 46) In the following section, we will present our annotation tagset, which allows us to tackle these issues.",
                "cite_spans": [
                    {
                        "start": 33,
                        "end": 41,
                        "text": "(Goethe,",
                        "ref_id": null
                    },
                    {
                        "start": 42,
                        "end": 45,
                        "text": "EA,",
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                    {
                        "start": 46,
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                        "text": "p. 46)",
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                "text": "The complete tagset is summarised in Table 2 . Because of the challenges associated with identifying restrictor and scope of a quantified statement, we do not annotate them separately. Instead, we label the whole span which contains quantifier, restrictor and scope. The tags in our tagset represent the (semantic) type of quantification. We take clauses as the smallest unit of annotation, meaning that one quantified statement may comprise one clause, as in (10), or several clauses, as in (11-12). Punctuation at annotation boundaries is omitted. We use brackets to indicate annotation spans and subscripts to denote tags. The following subsections motivate the individual tags.",
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                    {
                        "start": 37,
                        "end": 44,
                        "text": "Table 2",
                        "ref_id": "TABREF2"
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                "section": "A Tagset for Quantified Statements",
                "sec_num": "4"
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                "text": "Natural language employs a clear-cut set of mathematically precise quantifiers, whose meanings can be defined using set relations (see Table 3 ). All Table 3 : Truth conditions for precise quantifiers; S P := {x : P (x)} is the extension of P of these quantifiers are expressed by a number of lexemes at the surface of a sentence. \u2200 is expressed by all, every, always, everywhere etc., and MOST usually appears as most(ly) or main(ly). Statements with these quantifiers should be labelled with the tags ALL and MEIST (German for \"MOST\"), respectively:",
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                "ref_spans": [
                    {
                        "start": 135,
                        "end": 142,
                        "text": "Table 3",
                        "ref_id": null
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                        "start": 150,
                        "end": 157,
                        "text": "Table 3",
                        "ref_id": null
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                "section": "Precise Quantification",
                "sec_num": "4.1"
            },
            {
                "text": "Name Q Q[x : restr(x)][scope(x)] iff universal \u2200 |S restr \u2229 S scope | = |S restr | majority MOST |S restr \u2229 S scope | > |S restr \\ S scope | existential \u2203 |S restr \u2229 S scope | = 0 counting \u2203 Rn |S restr \u2229 S scope | R n proportional Q Rn/m prop |S restr \u2229 S scope | R n/m \u2022 |S restr |",
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                "section": "Precise Quantification",
                "sec_num": "4.1"
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                "text": "(13) There is lime, you remember, [which shows the strongest inclination for all sorts of acids-a distinct desire of combining with them] ALL . (Goethe, EA, p. 55 f.) 14[Men think most of the immediate-the present] MEIST ; (Goethe, EA, p. 16) \u2203 is associated with the indefinite article a/an in classical Fregean semantics (Zalta, 2020), as (15a) and (15b) exemplify. Fodor and Sag (1982) note, however, that a statement as in (15a) rather is ambiguous between the quantified interpretation in (15c) and the referential interpretation in (15d) (cf. von Heusinger, 2000) 1 . We follow this analysis and do not consider indefinite NPs to be markers for existential quantification. Instead, statements with a meaning as in (15c) are treated as genuine generic quantification (see Section 4.4): and statements with a meaning as in (15d) must not be labelled since they do not contain quantification.",
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                        "text": "(Goethe,",
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                        "text": "EA,",
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                        "start": 236,
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                        "text": "p. 16)",
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                        "start": 368,
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                        "text": "Fodor and Sag (1982)",
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            {
                "text": "(15) a. A man walks b. \u2203[x : man(x)][walk(x)] c. GEN[x : man(x)][walk(x)] d. walk(\u03b5 i x man(x))",
                "cite_spans": [],
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                "section": "Precise Quantification",
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                "text": "We use the tag EXIST for explicit existential statements instead. In English, such statements can be formulated with the expression there is/are or the verb exist:",
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                "section": "Precise Quantification",
                "sec_num": "4.1"
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                "text": "(16) [Thirdly, there are those people who investigate the sea bed as if it were a meadow] EXIST . (Fontane, Stechlin, p. 288) (17) [But they still do exist, they've got to exist or else they've got to exist again] EXIST . (Fontane, Stechlin, p. 130) There are different theories on how to analyse such existential statements, differing in the question whether existence is a quantifier or a predicate and, in case of the latter, what kind of predicate it is (McNally, 1998; Moltmann, 2013) . Although we do not have a preference for either analysis, we can observe that the verb exist must sometimes be analysed as a scope predicate rather than a quantifier. For example, it could be analysed either as existential quantifier or predicate of a covert quantifier in (18), whereas the quantifier analysis is not possible in (19) because of the overt quantifier MOST. The difference between (18b) and (18c) is very subtle and it is not always easy or even possible to identify the correct analysis-especially because a generic quantifier can also have an existential interpretation (Cohen, 2004) . Therefore, and because we prefer to keep all occurrences of exist in one class, we label all occurrences with EXIST and treat cases like 19 The last type of precise quantifiers are numerical quantifiers, which either express absolute counts (\u2203 Rn ) or proportions (Q Rn/m prop ). Numerical quantifiers are composed of numerals, such as one, two, half, third, dozen, hundred, percent, million, corresponding to n (and m). Numerals are optionally combined with an expression like at least, exactly, up to etc., corresponding to a mathematical relation R \u2208 {=, <, >, \u2264, \u2265, ...}: Numerical quantification should be labelled with the tag ZAHL (German for \"NUMBER\"): 2 (25) The county had always gone Conservative and it was a matter of honor to go Conservative again, as Luther had said, \"[Even if the world were full of a thousand devils] ZAHL .\" (Fontane, Stechlin, p. 140) The reader might argue that \"almost all\" as in (26) also has a mathematical definition (that is \"all but finitely many\") and should thus receive a separate tag. In natural language, however, almost modifies the truth value of a statement rather than its quantification (Kilbourn-Ceron, 2014). In fact, almost can appear in combinations with other quantifiers (see (27)) and without any quantifier (see (28)) as well, hence we do not include a separate tag for \"almost all\" in our tagset. We also treat similar modifiers like hardly, nearly, more or less etc. as not affecting the type of quantification. ",
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                        "start": 458,
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                        "start": 1938,
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                        "start": 1948,
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                        "text": "p. 140)",
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                "section": "Precise Quantification",
                "sec_num": "4.1"
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            {
                "text": "In addition to the precise quantifiers, one can find a broad range of vague quantifiers in natural language, whose truth conditions cannot be defined precisely. Some lexemes are few, some 3 , many,",
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                "ref_spans": [],
                "eq_spans": [],
                "section": "Vague Quantification",
                "sec_num": "4.2"
            },
            {
                "text": "2 A potentially conflicting case is Q >1/2",
                "cite_spans": [],
                "ref_spans": [],
                "eq_spans": [],
                "section": "Vague Quantification",
                "sec_num": "4.2"
            },
            {
                "text": "prop , which is mathematically equivalent to MOST. Following Hackl (2009) , who provides evidence for a cognitive difference between more than half and most, we label these expressions as follows: 3 The authors of this paper intensely discussed whether the German manch, which has a similar meaning to that of some, should be DIV or EXIST, because some scholars analyse manch/some as existential quantifier (e.g. L\u00f6bner, 2005; Chierchia and McConnell-Ginet, 2000, p. 310) . We decided to label manch with DIV since it usually implies an indefinite but rarely, occasionally, commonly, often; and multiword expressions like as a rule or in general can also express vague quantification. The vagueness makes it difficult to determine how many semantically different quantifiers there are-if not every lexeme represents its own quantifier. For example, is often the same as frequently? We therefore group all vaguely quantified statements under the tag DIV (for \"diverse\"): 29 ",
                "cite_spans": [
                    {
                        "start": 61,
                        "end": 73,
                        "text": "Hackl (2009)",
                        "ref_id": "BIBREF24"
                    },
                    {
                        "start": 413,
                        "end": 426,
                        "text": "L\u00f6bner, 2005;",
                        "ref_id": null
                    },
                    {
                        "start": 427,
                        "end": 471,
                        "text": "Chierchia and McConnell-Ginet, 2000, p. 310)",
                        "ref_id": null
                    }
                ],
                "ref_spans": [],
                "eq_spans": [],
                "section": "Vague Quantification",
                "sec_num": "4.2"
            },
            {
                "text": "As mentioned in Section 3, several quantifiers can occur within a statement; or several quantified statements can be nested as in (31). Annotations from overlapping statements do not affect each other, hence this is no multi-label case in the sense of having multiple tags for one statement. It can become a multi-label case if one merges tags on token or clause level, though, e.g. for measuring annotator agreement or evaluating a quantification tagger. Statements that contain more than one overt quantifier, on the other hand, should receive all corresponding tags, as in (32). We treat the assigned tags as a set, meaning that every of the five tags for overt quantification can be assigned only once to a statement, even if there are e.g. several quantifiers qualifying for the ALL tag, as in (33).",
                "cite_spans": [],
                "ref_spans": [],
                "eq_spans": [],
                "section": "Multiple Quantification",
                "sec_num": "4.3"
            },
            {
                "text": "(31) His entrance into the regiment more or less coincided with the beginning of the reign of Friedrich Wilhelm IV, [and whenever he mentioned that fact, he took pleasure in poking a bit of fun at himself by stressing that \"[all great events have their accompanying secondary phenomena] ALL .\"] ALL substantial (vague) number of entities (Dudenredaktion, n.d.) . (Furthermore, the determiner does not quite fit in the EXIST class from a morphological perspective.) We suggest that one should classify statements with some as DIV by the same argument. Note that manch always causes a quantificational interpretation (with singular and with plural NPs), whereas some can also cause a referential interpretation (like the indefinite article in (15d)) when combined with a singular NP (Winter, 1997) . In the latter case, no tag would be assigned. (Fontane, Stechlin, p. 3) The individual quantifiers within a statement do not always employ an unambiguous hierarchy, or the hierarchy becomes apparent after labourious semantic analysis only. Therefore, we do not opt for an ordering of the tags in the case of multiple quantification.",
                "cite_spans": [
                    {
                        "start": 338,
                        "end": 360,
                        "text": "(Dudenredaktion, n.d.)",
                        "ref_id": null
                    },
                    {
                        "start": 781,
                        "end": 795,
                        "text": "(Winter, 1997)",
                        "ref_id": "BIBREF50"
                    },
                    {
                        "start": 844,
                        "end": 866,
                        "text": "(Fontane, Stechlin, p.",
                        "ref_id": null
                    }
                ],
                "ref_spans": [],
                "eq_spans": [],
                "section": "Multiple Quantification",
                "sec_num": "4.3"
            },
            {
                "text": "There are more morphosyntactically complex quantifiers in natural language than we could discuss in the previous subsections (see Keenan and Paperno (2012) for an extensive overview). Complex quantifiers should be decomposed whenever no single tag is applicable, which can also result in a multi-label annotation:",
                "cite_spans": [
                    {
                        "start": 130,
                        "end": 155,
                        "text": "Keenan and Paperno (2012)",
                        "ref_id": "BIBREF31"
                    }
                ],
                "ref_spans": [],
                "eq_spans": [],
                "section": "Multiple Quantification",
                "sec_num": "4.3"
            },
            {
                "text": "(34) [All but two men walk] ALL+ZAHL",
                "cite_spans": [],
                "ref_spans": [],
                "eq_spans": [],
                "section": "Multiple Quantification",
                "sec_num": "4.3"
            },
            {
                "text": "In opposition to the other quantifiers discussed so far, the generic quantifier GEN is covert, i.e. it is not marked by a specific lexical item. Instead, there is a broad range of surface forms that can mark genericity. The statements in (35), for example, (cf. Carlson, 2011) We are aware that some semanticists would replace some of the generic quantifications in (37b) by existential quantifications or even nonquantificational expressions. This illustrates, however, how difficult it is to find covert generic quantifiers compared to overt quantifiers as in (38). With increasing complexity of sentence structures-as in fictional texts-, it is simply impossible to determine all covert quantifiers unambiguously in the annotation process. However, if no overt quantifier appears in a statement and the statement still has a quantificational meaning then there must be a covert quantifier somewhere. Hence quantified statements without any overt quantifier should be labelled with the tag BARE: 5 [The students from the towns and universities are sufficiently clever and orderly, but they are deficient in personal experience] BARE .",
                "cite_spans": [
                    {
                        "start": 262,
                        "end": 276,
                        "text": "Carlson, 2011)",
                        "ref_id": "BIBREF7"
                    }
                ],
                "ref_spans": [],
                "eq_spans": [],
                "section": "Generic Quantification",
                "sec_num": "4.4"
            },
            {
                "text": "Negation can occur in different syntactic positions and cause problematic cases during the annotation. If the quantifier or the scope in a universally or existentially quantified statement is negated, its meaning could be expressed as both a universal or existential quantification, following the negation rules for quantifiers:",
                "cite_spans": [],
                "ref_spans": [],
                "eq_spans": [],
                "section": "Negation",
                "sec_num": "4.5"
            },
            {
                "text": "(40) \u00ac\u2200[x : restr(x)][scope(x)] \u2261 \u2203[x : restr(x)][\u00acscope(x)]",
                "cite_spans": [],
                "ref_spans": [],
                "eq_spans": [],
                "section": "Negation",
                "sec_num": "4.5"
            },
            {
                "text": "5 It might be confusing why the passage about the country people in (39) is fragmented whereas the passage about the students is not. According to our annotation guidelines, two or more subsequent quantified statements should be joined if they receive the same tag and the restrictor or the scope stay the same. This condition is not fulfilled for the former passage where the restrictor firstly shifts from country people to their way of impairing it and the tag secondly changes from BARE to NEG. The case becomes even more complicated with ambiguous negation lexemes. The determiner no could be analysed as \u00ac\u2203 or \u00ac GEN, hence the statement in (42a) could be analysed as both 42b This means that one could find arguments to label (42a) with any of EXIST, ALL or BARE. Resolving (ambiguous) negation would require to know whether it applies to the quantifier, restrictor or scope of a statement, and a set of detailed definitions for how one should annotate cases as in (40) (41) (42) . Again, such a detailed analysis does not fit our aim of developing a simple annotation procedure. The simplest solution to this issue is to assign a special tag NEG for quantified statements with any negation in it. NEG then replaces all other tags that one could assign:",
                "cite_spans": [
                    {
                        "start": 971,
                        "end": 975,
                        "text": "(40)",
                        "ref_id": null
                    },
                    {
                        "start": 976,
                        "end": 980,
                        "text": "(41)",
                        "ref_id": null
                    },
                    {
                        "start": 981,
                        "end": 985,
                        "text": "(42)",
                        "ref_id": null
                    }
                ],
                "ref_spans": [],
                "eq_spans": [],
                "section": "Negation",
                "sec_num": "4.5"
            },
            {
                "text": "(43) \"[And there are many cases [...] in which we are obliged, and in which it is the real kindness, rather to write nothing than not to write] NEG .\" (Goethe, EA, p. 20) 5 Generalising Interpretations",
                "cite_spans": [
                    {
                        "start": 151,
                        "end": 159,
                        "text": "(Goethe,",
                        "ref_id": null
                    },
                    {
                        "start": 160,
                        "end": 163,
                        "text": "EA,",
                        "ref_id": null
                    },
                    {
                        "start": 164,
                        "end": 170,
                        "text": "p. 20)",
                        "ref_id": null
                    }
                ],
                "ref_spans": [],
                "eq_spans": [],
                "section": "Negation",
                "sec_num": "4.5"
            },
            {
                "text": "In the previous section, we presented a tagset for quantification. However, our research does not focus on quantified statements in general but only on generalising statements, which we consider to be a subset of quantified statements. The main purpose of our research is to find generalising statements in fictional works of literature to investigate their narratological function. Our working definition for generalisation results from previous work on the re-interpretation of universal quantifiers: L\u00f6bner (2005) already notes two interpretations for every (originally the German counterpart jede) as in (44), namely 1) a concrete quantification over contextually determined instances, and 2) a generic quantification over assumed instances. Similarly, Leslie et al. (2011) found that adults frequently judge universal statements as in (45) true, despite knowing that there are counterexamples. Leslie",
                "cite_spans": [
                    {
                        "start": 757,
                        "end": 777,
                        "text": "Leslie et al. (2011)",
                        "ref_id": "BIBREF37"
                    }
                ],
                "ref_spans": [],
                "eq_spans": [],
                "section": "Negation",
                "sec_num": "4.5"
            },
            {
                "text": "Instances assumed no (i) All students in the semantics class take notes (ii) All students in the semantics class are broke yes (iii) All triangles have three sides (iv) All ducks lay eggs Table 4 : Quantified statements with varying characteristics et al. 2011conclude that all can be interpreted as a generic quantifier instead of a universal quantifier, and calls this the \"generic overgeneralisation effect\".",
                "cite_spans": [],
                "ref_spans": [
                    {
                        "start": 188,
                        "end": 195,
                        "text": "Table 4",
                        "ref_id": null
                    }
                ],
                "eq_spans": [],
                "section": "Trueness erroneously accepted no yes",
                "sec_num": null
            },
            {
                "text": "(44) Every child is entitled to a place in school (45) All ducks lay eggs According to these works, an \"overgeneralised\" (universal) statement seems to be characterised by two properties:",
                "cite_spans": [],
                "ref_spans": [],
                "eq_spans": [],
                "section": "Trueness erroneously accepted no yes",
                "sec_num": null
            },
            {
                "text": "1. The quantification involves assumed instances, i.e. not all restricted instances are contextually determined.",
                "cite_spans": [],
                "ref_spans": [],
                "eq_spans": [],
                "section": "Trueness erroneously accepted no yes",
                "sec_num": null
            },
            {
                "text": "2. The statement is accepted as true (in the context of utterance) although there is not enough evidence for its trueness (because of unknown instances), or there is evidence for its falseness (because of known counterexamples).",
                "cite_spans": [],
                "ref_spans": [],
                "eq_spans": [],
                "section": "Trueness erroneously accepted no yes",
                "sec_num": null
            },
            {
                "text": "Quantified statements that fulfil both properties are clearly generalising whereas statements fulfilling none of them clearly are not. Statements that fulfil only one of the properties are harder to classify, which is why we want to briefly discuss them in the following.",
                "cite_spans": [],
                "ref_spans": [],
                "eq_spans": [],
                "section": "Trueness erroneously accepted no yes",
                "sec_num": null
            },
            {
                "text": "For examples (i) and (ii) in Table 4 , imagine a classroom situation in which all students take notes. Then there is no doubt that (i) is true. Furthermore, some (but not all) of the students look the worse for wear; hence there is not enough evidence to claim (ii) as being true. Thus, one could call (ii) a \"generalisation\" from a subset of the students to all of them, taking the ordinary meaning of \"generalisation\" into account. However, the additional (cognitive) process of generalising to any assumed instances is missing, which is why it is no generalising statement in our sense.",
                "cite_spans": [],
                "ref_spans": [
                    {
                        "start": 29,
                        "end": 36,
                        "text": "Table 4",
                        "ref_id": null
                    }
                ],
                "eq_spans": [],
                "section": "Trueness erroneously accepted no yes",
                "sec_num": null
            },
            {
                "text": "The restrictor in (iii) and (iv) includes all triangles or ducks, respectively. Hence the quantified instances include assumed/unknown instances. Still, even for triangles which one does not know, one can infer that they have three sides (because otherwise they would not be triangles by definition). Therefore, we do not consider such (quasi-) definitional statements (Leslie et al., 2011) to be generalising. 6 Having only looked at universal quantification so far, we now claim that generalisation can occur with every natural-language quantifier, and frequently does so in literary texts. Many of the examples shown in previous sections are in fact generalising; additional examples for each tag are given in the appendix (A). Unlike Leslie et al. (2011) and L\u00f6bner (2005) , we do not claim that the quantifier in a generalising statement is re-interpreted as generic quantifier. Based on our observations (cf. Sec. 6), we suppose that generic quantification is a frequent but not the only type of quantification used to express generalisation.",
                "cite_spans": [
                    {
                        "start": 369,
                        "end": 390,
                        "text": "(Leslie et al., 2011)",
                        "ref_id": "BIBREF37"
                    },
                    {
                        "start": 411,
                        "end": 412,
                        "text": "6",
                        "ref_id": null
                    },
                    {
                        "start": 738,
                        "end": 758,
                        "text": "Leslie et al. (2011)",
                        "ref_id": "BIBREF37"
                    },
                    {
                        "start": 763,
                        "end": 776,
                        "text": "L\u00f6bner (2005)",
                        "ref_id": null
                    }
                ],
                "ref_spans": [],
                "eq_spans": [],
                "section": "Trueness erroneously accepted no yes",
                "sec_num": null
            },
            {
                "text": "We currently construct a diachronic corpus of German fictional literature from 1650 to 1950. As of now, we annotated generalising interpretations in ten texts-excluding some additional texts from a pilot annotation for developing our annotation guidelines. CATMA 7 appeared to be most suitable for annotating fictional texts and became our tool of choice. In order to create a versatile dataset and save resources, we annotate only the beginning of every text (usually the first about 200 sentences).",
                "cite_spans": [],
                "ref_spans": [],
                "eq_spans": [],
                "section": "Corpus and Annotations",
                "sec_num": "6"
            },
            {
                "text": "Our annotation procedure is as follows: Each text is first annotated by two out of six student assistants. In a second step, two researchers glance over the text again, focusing on the statements that were annotated by at least one annotator, discuss the annotations and create an expert annotation as gold standard. Arguably, this procedure is prone to false negatives, i.e. statements that none of the annotators identified are likely to be missed while creating the gold standard.",
                "cite_spans": [],
                "ref_spans": [],
                "eq_spans": [],
                "section": "Corpus and Annotations",
                "sec_num": "6"
            },
            {
                "text": "We measure inter-annotator agreement on tokenlevel (excluding punctuation) using \u03ba (Fleiss et al., 2003) , treating the occurring tag combinations as 6 Generic is not the same as generalising by our definition: Since generic quantification can also be used to express definitional statements (e.g. triangles have three sides), not all generic statements are generalising statements.",
                "cite_spans": [
                    {
                        "start": 83,
                        "end": 104,
                        "text": "(Fleiss et al., 2003)",
                        "ref_id": "BIBREF13"
                    },
                    {
                        "start": 150,
                        "end": 151,
                        "text": "6",
                        "ref_id": null
                    }
                ],
                "ref_spans": [],
                "eq_spans": [],
                "section": "Corpus and Annotations",
                "sec_num": "6"
            },
            {
                "text": "7 https://catma.de/ GI+Q GI Q \u03ba \u03c3 \u03ba \u03c3 \u03ba \u03c3 .67 .20",
                "cite_spans": [],
                "ref_spans": [],
                "eq_spans": [],
                "section": "Corpus and Annotations",
                "sec_num": "6"
            },
            {
                "text": ".68 .22 .85 .14 classes (i.e. none, ALL, ..., ALL+DIV, ...). Since the annotators vary between texts, we first compute the agreement separately for each text. The average agreement is shown in Table 5 . On average, there is substantial agreement of 0.67 for annotating generalising statements (GI+Q). The relatively high standard deviation of 0.20 indicates that there is a great variance between texts and/or annotators. Additionally, we compute the agreement when just distinguishing between \"no tag\" and \"any tag\", i.e. \"not generalising\" vs. \"generalising\" (GI). The values are almost identical to those for GI+Q, indicating that the overall agreement is mainly influenced by the agreement on what is a generalising interpretation. To estimate the applicability of our tagset, we also compute the agreement for only those tokens that received a tag by all annotators, i.e. those tokens where the annotators agreed that they are part of a generalising statement (Q). Here, we see an average agreement of 0.85, which is significantly higher than that for GI, indicating that annotating quantification is comparatively straightforward. Annotation results can be found in Table 6 . Within 2,791 annotated sentences (61,979 tokens), 728 generalising statements occur (in the gold standard), which have an average length of 17 tokens. We can see that most generalising statements use plain generic quantification (BARE); followed by universal quantification (ALL) and vague quantification (DIV). Generalising statements with existential quantification (EXIST) or majority quantification (MEIST) are far less common. Note, however, that the counts do not directly reflect a \"generalisation potential\" of the individual quantification types since some quantification types occur with a higher frequency than others in the first place. We removed the tag ZAHL from our annotation guidelines because generalising interpretations for numerical quantifiers hardly occurred during the pilot annotation (and ever since then).",
                "cite_spans": [],
                "ref_spans": [
                    {
                        "start": 193,
                        "end": 200,
                        "text": "Table 5",
                        "ref_id": "TABREF10"
                    },
                    {
                        "start": 1172,
                        "end": 1179,
                        "text": "Table 6",
                        "ref_id": "TABREF11"
                    }
                ],
                "eq_spans": [],
                "section": "Corpus and Annotations",
                "sec_num": "6"
            },
            {
                "text": "While the data in the existing corpora that are annotated with phenomena related to generalisation usually originates from the domains traditional for NLP, such as news and internet communication, we investigate generalisation in fiction, a more complex domain. To the best of our knowledge, there are no corpora on generalisation or genericity for German and our work reduces this gap.",
                "cite_spans": [],
                "ref_spans": [],
                "eq_spans": [],
                "section": "Related Work",
                "sec_num": "7"
            },
            {
                "text": "Most existing resources focus on noun phrases, often in the context of coreference resolution. A detailed survey on generics in the coreference resolution research can be found in Nedoluzhko (2013) . Friedrich et al. (2015) provide a survey of genericity-annotated corpora for English. They note that ACE corpora (Mitchell et al., 2003; Walker et al., 2006) are most widely used, e.g. by Reiter and Frank (2010) , to identify generic noun phrases using a supervised approach. Friedrich et al. (2015) were the first to suggest an annotation scheme for generic statements where both clauses and their subject NPs are annotated with the labels \"generic\" and \"non-generic\". However, they only consider kind-referring generics and exclude e.g. habitual statements. In a subsequent work, Friedrich et al. (2016) investigate both habituals and kind-referring generics as two separate situation entity types, alongside with states and events, in a sentence classification task.",
                "cite_spans": [
                    {
                        "start": 180,
                        "end": 197,
                        "text": "Nedoluzhko (2013)",
                        "ref_id": "BIBREF44"
                    },
                    {
                        "start": 200,
                        "end": 223,
                        "text": "Friedrich et al. (2015)",
                        "ref_id": "BIBREF19"
                    },
                    {
                        "start": 313,
                        "end": 336,
                        "text": "(Mitchell et al., 2003;",
                        "ref_id": "BIBREF42"
                    },
                    {
                        "start": 337,
                        "end": 357,
                        "text": "Walker et al., 2006)",
                        "ref_id": "BIBREF49"
                    },
                    {
                        "start": 388,
                        "end": 411,
                        "text": "Reiter and Frank (2010)",
                        "ref_id": "BIBREF46"
                    },
                    {
                        "start": 476,
                        "end": 499,
                        "text": "Friedrich et al. (2015)",
                        "ref_id": "BIBREF19"
                    },
                    {
                        "start": 782,
                        "end": 805,
                        "text": "Friedrich et al. (2016)",
                        "ref_id": "BIBREF20"
                    }
                ],
                "ref_spans": [],
                "eq_spans": [],
                "section": "Related Work",
                "sec_num": "7"
            },
            {
                "text": "Many of the existing works use a limited set of labels: generic/non-generic or generic/specific. Herbelot and Copestake (2010, 2011) use a tagset similar to ours: ONE, SOME, MOST, ALL, QUANT. However, their concept is quite different: The authors assume that covertly quantified NPs are not generic but underspecified and label those NPs according to how many members of a class they refer to. Bhakthavatsalam et al. (2020) create a large knowledge base of generic statements. The metadata in this knowledge base includes the term (restrictor) and the quantifier. They also include statements with an overt quantifier but \"generic interpretation\".",
                "cite_spans": [
                    {
                        "start": 394,
                        "end": 423,
                        "text": "Bhakthavatsalam et al. (2020)",
                        "ref_id": "BIBREF3"
                    }
                ],
                "ref_spans": [],
                "eq_spans": [],
                "section": "Related Work",
                "sec_num": "7"
            },
            {
                "text": "Contrasting the previously mentioned shallow annotation schemes, Bunt et al. (2018) / Bunt (2019) propose an annotation scheme for quantifi-cation that consists of several layers for syntactic and semantic representations but does not incorporate solutions for generics/habituals, yet. Donatelli et al. (2019) suggest to expand the existing Abstract Meaning Representation (AMR) framework for the semantic annotation of sentences (Banarescu et al., 2013) by marking aspect and tense. As for aspect, they include such categories as \"habitual\" that characterise a regular recurrence of an event or state, and \"stable\" that characterises states and includes generalisations over kinds.",
                "cite_spans": [
                    {
                        "start": 286,
                        "end": 309,
                        "text": "Donatelli et al. (2019)",
                        "ref_id": "BIBREF11"
                    },
                    {
                        "start": 430,
                        "end": 454,
                        "text": "(Banarescu et al., 2013)",
                        "ref_id": "BIBREF1"
                    }
                ],
                "ref_spans": [],
                "eq_spans": [],
                "section": "Related Work",
                "sec_num": "7"
            },
            {
                "text": "In comparison to the discussed approaches, we do not limit ourselves to NPs or clauses but annotate entire statements. Our tagset provides tags for overt quantification as well as covert generic quantification. Regarding the annotation of generalising statements, we jointly consider generalisations about entities, events and other types, that have been predominantly studied separately in the past.",
                "cite_spans": [],
                "ref_spans": [],
                "eq_spans": [],
                "section": "Related Work",
                "sec_num": "7"
            },
            {
                "text": "In this paper, we presented an annotation scheme for quantified phenomena using the example of generalisation. Our tagset matches every quantifier occurring in natural language to a particular tag, based on semantic criteria. We propose a shallow annotation that combines quantifier, restrictor and nuclear scope into a common annotation span, where the smallest unit of annotation is a clause. This approach is suitable for large-scale annotations which aim to investigate the distribution of quantified phenomena in a corpus, or to mark quantified statements to serve as feature input in followup applications. As a first step in this direction, we introduce our corpus of fictional texts that are annotated with generalising interpretations (among other phenomena). 8 Moreover, we are working on an automatic tagger for generalising statements.",
                "cite_spans": [],
                "ref_spans": [],
                "eq_spans": [],
                "section": "Conclusion and Future Work",
                "sec_num": "8"
            },
            {
                "text": "The expression \u03b5ix P (x) returns an entity which satisfies the predicate P , based on the choice function i(Avigad and Zach, 2020).",
                "cite_spans": [],
                "ref_spans": [],
                "eq_spans": [],
                "section": "",
                "sec_num": null
            },
            {
                "text": "Ignoring tense. The German pflegen zu 'use to' can also be used in present tense; unfortunately, there seems to be no equivalent present-tense construction in English.",
                "cite_spans": [],
                "ref_spans": [],
                "eq_spans": [],
                "section": "",
                "sec_num": null
            },
            {
                "text": "Our corpus and annotation guidelines are accessible at https://gitlab.gwdg.de/mona/ korpus-public.",
                "cite_spans": [],
                "ref_spans": [],
                "eq_spans": [],
                "section": "",
                "sec_num": null
            }
        ],
        "back_matter": [
            {
                "text": "Our special thanks go to Anke Holler and the other members of the MONA project group, who advised us on the development of this work. We further thank the anonymous reviewers for their valuable comments. This work is funded by Volkswagen Foundation (D\u00f6nicke, G\u00f6deke), and by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) -424264086 (Varachkina).",
                "cite_spans": [],
                "ref_spans": [],
                "eq_spans": [],
                "section": "Acknowledgements",
                "sec_num": null
            },
            {
                "text": "A Examples for Quantified Statements with Generalising Interpretations (46) [In all natural objects with which we are acquainted, we observe immediately that they have a certain relation to themselves] ALL . (Goethe, EA, p. 53) (47) [Heroism is the exception] BARE [and mostly the product of a separate situation] MEIST . (Fontane, Stechlin, p. 19) (48) [But there are also fruits which are not outward, which are of the true germinal sort, and which develop themselves sooner or later in a beautiful life] EXIST . (Goethe, EA, p. 43) (Fontane, Stechlin) ",
                "cite_spans": [
                    {
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                "content": "<table><tr><td/><td colspan=\"3\">: Mean inter-annotator agreement (\u03ba) over all</td></tr><tr><td colspan=\"4\">texts and corresponding standard deviations (\u03c3); see</td></tr><tr><td colspan=\"3\">text for column meanings</td><td/></tr><tr><td/><td colspan=\"3\">Generalising statements</td></tr><tr><td colspan=\"4\">ALL MEIST EXIST DIV BARE NEG Total</td></tr><tr><td>151</td><td>7</td><td>17 76</td><td>332 145 728</td></tr></table>",
                "html": null,
                "num": null
            },
            "TABREF11": {
                "text": "Number of generalising statements in all texts",
                "type_str": "table",
                "content": "<table/>",
                "html": null,
                "num": null
            }
        }
    }
}