A sea of choices: lexical quantifiers in English and German

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Правительство Российской Федерации

Федеральное государственное автономное образовательное

учреждение высшего образования

Национальный исследовательский университет

“Высшая школа экономики”

Факультет гуманитарных наук

Образовательная программа

“Фундаментальная и компьютерная лингвистика”

Выпускная квалификационная работа студента 4 курса бакалавриата группы БКЛ 141

МОРЕ ВЫБОРА: ЛЕКСИЧЕСКИЕ КВАНТИФИКАТОРЫ В АНГЛИЙСКОМ И НЕМЕЦКОМ ЯЗЫКАХ (A SEA OF CHOICES: LEXICAL QUANTIFIERS IN ENGLISH AND GERMAN)

Стырина Софья Константиновна

Академический руководитель образовательной программы

канд. филологических наук, доц. Ю.А. Ландер

Научный руководитель канд. филологических наук, доц.

Т.И. Резникова

Москва 2018

Table of contents

Introduction

Literature review

Chapter I. Collecting data

Chapter II. English quantifiers

Chapter III. German quantifiers

Chapter IV. Further German & English quantifier analysis

Conclusion

References

Appendix

Introduction^** The author would like to thank Professor Tatiana Reznikova, my scientific advisor, for the valuable guidance and constructive criticism throughout the production of the current thesis.

Literature review

The current study concerns constructions with a certain grammatical structure that imposes restrictions on the elements that may appear as the construction's variables. The most fitting framework for studying entities of this kind is Construction Grammar. The framework was first outlined by Charles Fillmore, starting with the paper Fillmore et. al 1988 “Regularity and Idiomaticity in Grammatical Constructions: The Case of Let Alone”. In this publication Fillmore voices criticism regarding the traditional, or “the atomistic view of complex linguistic objects”, wherein a speaker possesses the following knowledge, which is proposed as being sufficient to formulate any legitimate sentence in a given language: 1) knowledge of the lexical information; 2) knowledge of the elementary grammatical rules of combining words into simple phrases, and simple phrases into more complex structures; and 3) the pragmatic and semantic principles, which allow to interpret the meaning of words and sentences in various context. Fillmore proposes an alternative theory of Construction Grammar, based on the claim that certain grammatical constructions are impossible to interpret based solely on the principle of compositionality, which, to a certain degree, makes them idiomatic. According to Fillmore, these constructions contain not only syntactic information, but also semantic, pragmatic and lexical information, which is not readily available from the compositional meaning of the construction's elements.

Construction Grammar served as the foundation of several monographic works of Adele Goldberg (Goldberg 1995, Goldberg 2006), which positively contributed to the popularity of Fillmore's theory. Russian linguists have also approached this field of study, including Ekaterina Rakhilina (Rakhilina 2010) and Leonid Iomdin, who dubbed it “microsyntax”. Iomdin's works focus on the study and description of nonstandard and peripheral syntactic constructions in Russian, i.e. his paper on the phraseological units в силу, от силы, в x-овую силу (`v silu', `ot sily', `v x-ovuju silu') and two separate predicative units в силах (`v silah') (Iomdin 2008).

The lexemes in the spotlight of the present study came to function as quantifiers as a result of grammaticalization. Therefore, it seems relevant to assess the extent of grammaticalization undergone by each quantifier as part of their overall analysis. The criteria for this assessment were outlined in the works that explored and constructed the theory of grammaticalization (including Lehmann 1995; Hopper, Traugott 2003). These criteria are based on the appearance of changes that include 1) semantic bleaching, or loss of semantic substance, 2) phonological reduction, 3) morphological reduction, and 4) obligatorization (an entity becoming obligatory in certain morphosyntactic contexts), the first and last of which will be relevant for the analysis of lexical quantifiers in German and English.

Adrienne Lehrer (Lehrer 1986) undertook the topic of classifier constructions in English, aiming to explore the taxonomy of classifiers, as well as the nature of the restriction between the classifier and the noun phrase it can pertain to. The study also focused on the syntax and the semantics of English classifiers, and the semantic interpretation of novel or atypical contexts of classifier constructions. Lehrer utilizes the taxonomy of English classifiers proposed by Keith Allan (Allan 1977), in which he roughly identifies seven different categories:

1. Unit counters: a cube of ice, a sheet of aluminium foil

2. Fractional classifiers: two thirds of an apple

3. Number set classifiers: thousands of buildings, hundreds of tasks

4. Collective classifiers: a litter of puppies, a flock of geese

5. Varietal classifiers: two types of beer, five breeds of horses

6. Measure classifiers: three ounces of sugar, a kilometer of terrain, an armful of books

7. Arrangement classifiers: a line of cars, a tower of dishes

Lehrer points out that while measure classifiers may indicate exact quantities (a yard of rope, a dozen of books), the rest of them appear to vaguely allude to a quantity of a certain item or concept (oodles of poodles, for instance, indicates a large number of dogs, but it's hard to judge as to the exact number meant by the speaker). The motivation for choosing a specific noun as the classifier often lies in the shape or formation of a particular multitude or, alternatively, may indicate the container that is typically used to hold it. This partially explains why some classifiers are applicable to specific nouns or a very limited group (a loaf of bread, a flock of geese), while others demonstrate quite an extensive variety of collocations (e.g. a bunch of trees/people/apples/stories/errands). It's also possible to interpret one classifier as belonging to several categories (a bowl of milk, for instance, may indicate the amount of liquid that typically fits in one bowl, or the container holding the milk). It's important to note, as Lehrer mentions, that “since English does not require a classifier with count nouns, the use of one should serve some purpose” (Lehrer 1986, p. 131). The use of a classifier in atypical collocations may transfer a certain association of the classifier noun to the object being described (such as a mob of people adding certain negative judgment about a group of individuals). Thus, for a thorough interpretation of English classifier expressions it's crucial that semantic and pragmatic information is taken into account alongside lexical and collocational information.

Tony McEnery and Richard Xiao have also explored the topic of quantifying constructions. One of their co-authored papers (McEnery, Xiao 2007) focused on the grammatical class of classifiers in Chinese and compared them to quantifying constructions in English. McEnery and Xiao examined data from two corpora for each language: one collection consisting of written texts and the second collection containing transcripts of phone conversations.

The mandatory use of classifiers in Chinese (which are either borrowed ad hoc from the class of nouns or act solely as fully grammaticalized classifiers) for quantifying nouns provides ample material to implement a taxonomy of classifiers based on semantics. McEnery and Xiao used this approach to divide Chinese classifiers into eight categories, borrowing unit, collective, varietal (species), measure and arrangement classifiers from Allan's taxonomy, and adding three other types of classifiers: container (a bottle of Chardonnay), temporal (measuring the duration of a situation, e.g. two hours of driving) and verbal (that indicate how many times an action or event occurred). They concluded that English lexemes that are used as quantifiers in the construction numeral + quantifying noun + of + noun (a row of chairs, a roomful of doctors) are also able to fit into the same semantic categories. McEnery and Xiao also argue that, despite the syntactic differences between Chinese and English (e.g. the notion that English classifiers are only mandatory to use when quantifying non-countable nouns), English and Chinese classifiers should not continue to be treated as two separate phenomena. They support this idea by presenting pragmatic, cognitive, and conventional motivation for the use of the classifier class in both languages. Nevertheless, it's important to note that the English quantifying constructions which employ classifiers are far less frequent compared to their Chinese counterpart (the authors do mention them being 29 times less common in English). This notion does continue to justify the prevalent view that English should not be perceived as a language with a distinct grammatical class of classifiers.

The topic of lexical quantifiers has also been examined by Ekaterina Rakhilina for Russian data. Chapter 2 in the third part of the book “Linguistics of Constructions” (Rakhilina 2010) focuses on Russian nouns that initially represented tangible objects, and later gained use as a lexical quantifier (N₁) that indicated a large quantity (of N₂) in the construction N₁(Nominative) + N₂ (Genitive) (e.g гора посуды -- `a mountain of dishes'). The nouns occupying the N₁ position experience a semantic shift and partial grammaticalization, and also attribute a certain connotation or appraisal in regard to the object in the N₂ position (in other words, they add extra meaning to the object in N₂ that is unrelated to quantity).

Rakhilina introduces a systematic approach to classifying Russian lexical quantifiers based on several parameters, some of which correlate with Allen's taxonomy of classifiers. A significant innovation in Rakhilina's approach compared to the previous works on quantifiers and their taxonomy is the consideration of how the various quantified multitudes of objects relate to an individual person that interacts with them. This notion is reflected in the choice of parameters for analyzing the corresponding quantifiers. The first set of parameters evaluates the qualities of the quantifying lexemes. Those parameters include 1) motion (i.e. whether the object indicated by the quantifier is typically in motion, such as река слез -- `a river of tears'), and the direction of that motion from the speaker's perspective, 2) connotation (positive or negative), 3) heterogeneity (whether the objects in a multitude are of one type or several), 4) purpose (whether the multitude of objects is intended for future use), and 5) usefulness (of the multitude of objects). The second set of parameters deals with the qualities of the objects in a given quantity, namely 1) vertical position and 2) weight. The next group unites parameters of the group of objects as a whole: 1) order (whether the objects are arranged in a certain way or are all positioned randomly), 2) consistency or expectancy of the situation (whether the quantified events take place suddenly and simultaneously or in a sequence), repetition (based on the notion that using the plural form of the quantifier indicates a repetition of the situation that involves a multitude of objects or events), and 3) whether a given multitude of objects increases in number over time. And finally, another important parameter is the semantic source of the metaphor at work that allows a certain lexeme to become a quantifier of multitude. Rakhilina also proposes to pay attention to the degree of semantic bleaching and grammaticalization of a given lexical quantifier (particularly, whether it's able to quantify abstract nouns, animate nouns and adjectives). In the current paper, this extensive principle of systemization is tested on lexical quantifiers outside of Russian, namely in the two Germanic languages discussed in the introduction.

Chapter I. Collecting data

Identifying the most frequently used lexical quantifiers (in this paper also referred to as LQs) was the first major task within the current research project. A brief look into lexicographical resources yielded a handful of synonyms for multitude and Vielzahl (for English and German respectively) that were viable for the study. However, it was also necessary to employ corpus data to gather a more comprehensive list of sought after lexemes, as well as the information on which entities they are used to quantify. The following table (Table 1) presents a brief summary of initial data collection results, including the Sketch Engine corpora used for gathering data, as well as the exact search queries, and the results they produced.

As shown in Table 1, the sought after “multitude” quantifiers were identified as they appeared in the widespread nominal construction a/an N_SG of N_SG/PL and ein/eine N_{NOM SG} von N _{DAT SG/PL} in English and German respectively. In both phrases the head noun (on the left) may act as the indicator of units in which the entity presented by the second noun is counted (e.g. a box of mice, ein Wald von Bдumen -- a forest of trees). There are, of course, other ways in which both of these constructions are used (e.g. an enemy of sorts, ein Problem von Mдnnern -- a problem of men/men's problem, ein Geschenk von Mary -- a present from Mary), which are not connected with the subject of the present study, and therefore not examined. Furthermore, German has some variations of the quantifier phrase, such as ein/eine N_{NOM SG} N _{GEN SG/PL}, which is devoid of the preposition von (e.g. ein Glas Wasser -- a glass of water). It was decided, however, to conduct the corpus search using the query that included the preposition von, in hopes of decreasing the ratio of noise (consisting of other nominal phrases that contain two nouns) to the sought after construction use.

As also seen in Table 1, the corpus search results were quite numerous (accumulating several millions hits in both enTenTen13 and deTenTen13 corpora). Therefore, a 10 000 size sample for both English and German results was manually analyzed to find the sought after lexical quantifiers of multitude. As a result, a preliminary list of approximately 50 German quantifiers and 100 English quantifiers were collected. Both lists are presented in Table 2 and Table 3 in the Appendix, including the frequency of each quantifier in the appropriate 10 000 corpus sample. In order to maximize the attention devoted to the examination of each quantifier, it was decided to only select the most frequently occurring units in both languages. It's worth noting that only concrete nouns were chosen to for further examination, as that was the case for the study of multitude lexical quantifiers in Russian (Rakhilina 2010), which the course of the following quantifier analysis will heavily rely on. Below are two lists of the selected multitude quantifiers, for English and German respectively:

26 English quantifiers: crowd, host, army, flock, bevy, swarm, sea, ocean, stream, wave, flood, spate, flurry, avalanche, fleet, arsenal, pile, stack, bundle, chain, string, web, litany, barrage, world, explosion.

25 German quantifiers: Heer -- army, Schar -- crowd, Armee -- army, Horde -- horde, Schwarm -- swarm, Wolke -- cloud, Meer -- sea, Ozean -- ocean, Strom -- stream, Welle -- wave, Schwall -- barrage, Flut -- flood, Lawine -- avalanche, Kaskade -- cascade, Hagel -- hail, Armada -- armada, Arsenal -- arsenal, Bьndel -- bunch, bundle; Haufen -- heap, Wand -- wall, Berg -- mountain, Kette -- chain, Labyrinth -- maze, Sturm -- storm, Feuerwerk -- firework.

As can be seen in Table 2 and Table 3 (provided in the Appendix), the examples of quantifying constructions from the 10 000 corpus samples that contain the selected English and German quantifiers noticeably vary in quantity (for example, an army of N_SG/PL gathered over 400 hits, while an ocean of N_SG/PL accumulated only about 60 occurrences). To balance out the data used for further analysis, a new collection of samples was taken from the enTenTen13 and deTenTen13 corpora, consisting of approximately 100 samples containing each selected quantifier (thus assembling about 3000 and 2800 samples for English and German respectively). The search queries used for collecting this new data contained the same format that appears in Table 1, with the specific quantifier in place of the second bracket (i.e. [word=“a”] [tag="flock"] [word="of"] [tag="NNS"]).

Chapter II. English quantifiers

The first angle for examining and comparing the selected lexical quantifiers in English (and later in German) is the type of quantified entity that each quantifier tends to occur with, both from a synchronic and diachronic perspective. In order to complete the overview of how each quantifier first came into use as such and how its application has changed over time, it was necessary to combine corpus data and historical lexicographical resources.

Specifically for investigating the present state of each quantifier's typical context of use, it was fitting to employ the 100-sample data gathered for each quantifier in the top-26 list. First, a list of all quantified nouns from this sample data was gathered, after which those list members were manually split into approximate semantic groups. The first and foremost factor for forming these groups was the separation of physical objects and abstract notions. Physical objects were further divided into animate (humans and animals) and inanimate objects (tangible countable objects and substances). Abstract notions were slightly harder to classify, and were roughly split into the following:

1) notions of the human internal world (emotions, feelings, and character traits);

2) sensory perception (everything that could be heard, tasted, etc.; admittedly, this group is closer to the physical realm, but it excludes any objects that can be held and touched, which were united under the previously mentioned “physical objects” category);

3) a group that combined various events, activities, and occurrences of actions;

4) everything pertaining to speech, text, information, and media (music, film, news, etc.)

5) other intangible notions, that were hard to classify as any of the previous groups.

The classification system described above was then used to cluster the top-26 English lexical quantifiers of multitude based on which types of entities they typically appear with in present-day language use. Table 4, located below, illustrates the classification results. Of course, it should be noted that each word in the table does not exclusively quantify the type of entity under which it is listed, which will be discussed in more depth below.

The multitude quantifiers form 3 groups. The first group is comprised of 9 lexemes that are primarily used to quantify physical entities. The group further divides into lexemes that are primarily used to describe a multitude of people (crowd, army), as well as animals (flock, swarm) and countable inanimate objects (pile, stack, fleet, sea). The second group is more commonly used with abstract entities, while the words in the third group are roughly equally used with both mentioned types. The “mixed” group is made up of 12 quantifiers on the top-26 list, while the group primarily for abstract notions has just 6 members. Abstract notions are also divided into several groups: a group combining human emotions (quantified by wave), a group of events, activity, and other types of occurrences (quantified by flurry, litany, and spate), and notions related to information and speech, which appear in a considerable portion of sample data for explosion and avalanche.

Already we can see a pattern in these groups of quantifiers: people and other live creatures are most often “quantified” by words with meanings directly associated with people and animals. On the other hand, inanimate physical objects and abstract notions appear most with quantifying lexemes that themselves indicate inanimate objects as well (wave, explosion, web, avalanche, etc.), albeit with the exception of host. With that in mind, it's time to look at these 26 English quantifiers from a diachronic perspective and see what changes in their combinability with certain entities have occurred over time.

For this diachronic investigation, an examination of the dictionary entries for each English lexeme was conducted, tending to contemporary definitions and any available etymological notes on the shift of applicable contexts throughout various time periods. After completing that step, it was possible to build a schematic chain, beginning with the earliest relevant denotation of the future lexical quantifier, followed by any changes in meaning and applicable context that enabled the meaning of “multitude”. The results were used to split the quantifiers in groups based on the semantic origin of each particular quantifier, which, as will be shown below, usually aligned with the context shifts that the group members experienced. The examples for illustrating the use of quantifiers will be taken from the corpus data discussed above.

The first group of quantifiers consists of words that initially indicate a large amount of humans and other live creatures. Table 5, positioned directly below, lists the quantifiers in this group and illustrates the dynamic of the quantified entities they apply to. The arrows indicate that the element directly to the right of the symbol came to be “quantified” at a later time than the element preceding the arrow. It does not necessarily mean that the earlier entity has fallen out of use once the latter entity appeared.

As reflected in the table, the 6 members of this group are divided into pairs of words that have gone through a similar series of shifts in the type of entity they can quantify. The first pair is composed of crowd and host, both originally used to indicate a large number of human beings. The term crowd has been used to describe a multitude of people since at least the XVI century, while host was first used in English to indicate a multitude of foreign people, and soon after -- armed forces. Eventually, large non-military groups of humans were also quantified using host (a host of friends, a host of designers and artists). While crowd is still primarily used for the description of people (although rarely beginning to appear to “count” abstract notions, e.g. (a crowd of sorrows, a crowd of messages), host has widened its scope of also quantifying countable physical objects (a host of frigates, a host of restaurants), and also various abstract notions (a host of questions, a host of reasons, a host of experiences). The corpus data suggests that the latter two types of entities are now the primary context for the quantifier host, as it is now used considerably less often to talk about big groups of people.

The second pair of similar quantifiers in the “people” and “animal” quantifier group is made up of army and flock. While originally used to denote sea and land expeditions, army has claimed the transferred meaning of “multitude” sometime in the XVI century, and during that time also came to be used to describe a multitude of armed men that were trained for war. Flock has a slightly different origin story: in Old English is was used to quantify humans only, and sometime in the XIII century was extended to indicate domestic animals that moved and fed as one whole group (such as a flock of sheep). Later, flock was also used to quantify the multitude of Christians, in the sense that they were a flock with Christ -- their pastor. Since the XIX century flock became widely used in contexts involving birds (a flock of pigeons, a flock of geese). Other animals also eventually started to become “quantified” using army (an army of worms, an army of puppies). Corpus data relevant to the quantifier use of army and flock shows that both may appear to describe a multitude of countable physical objects (a flock of plates, a flock of neighborhood houses; an army of taxis, and army of factories). Both quantifiers remain applicable to large groups of people (an army of volunteers, a flock of waiters), although flock is prevalent in contexts pertaining to animals.

The last two words in the first group are bevy and swarm. The former started out as a collective noun for women and quails (a species of birds), while swarm was first used to indicate a cloud of moving bees or other insects, and later -- bats. Later both words became applicable for quantifying people (a bevy of experts, a swarm of women). Corpus data also shows bevy sometimes appearing as a quantifier for inanimate physical objects (a bevy of flowers, a bevy of drones), and both bevy and swarm -- as indicators of a large sum of abstract notions (a bevy of questions, a bevy of improvements; a swarm of ideas, a swarm of education polls). While bevy retains a large scope of the types of contexts it can appear in, swarm remains to be used primarily as a quantifier for flying insects.

Overall, the English words in the “people” and “animal” quantifier group follow a similar path in terms of widening their scope of applicable quantified entities. Starting out as a lexical quantifier for people and animals, they evolve to act as quantifiers for inanimate physical objects and eventually for abstract notions. However, at this point in time they are quite varied in regard to the type of entity they are most frequently used to describe.

The next group of English quantifiers to be discussed is quite an extensive cluster of words, the meanings of which are directly related to water. Table 6, placed below, lists the members of this group and the various contexts of their application. As the table also shows, this group is further divided into two. The first subgroup unites lexemes that describe a body of water: sea and ocean.

The first word sea is attested to have appeared as a general lexical quantifier of multitude approximately since the XIII century. The corpus data shows that the scope of entities quantified with sea is indeed quite diverse, including both tangible physical objects (a sea of candles, a sea of leaves), people (a sea of tourists), and abstract notions (a sea of dreams, a sea of contradictions, a sea of abbreviations). When used to describe an enormous groups of people in one place, it's likely that the observer of such “body” is looking down at it from a higher point, thus able to perceive a multitude of standing or moving people as a flatter mass. It is hypothesised that the quantifier's use in contexts relating to people is recent (relevant to that of physical objects and abstract notions), based on the claim that the application to animate entities is a strong indication that the lexical quantifier is at a significantly advanced stage of grammaticalization (given that the initial meaning of the quantifier is quite distant from denoting humans and animals) (Rakhilina 2010, p. 393).

The other member of the first subgroup of “body of water” quantifiers (ocean) seems to follow a very similar path to that of sea. It may be used to exaggerate a description of a particular substance (an ocean of blood being the most prominent example), and at other times to use that description to intensify the account of a certain situation (e.g. using an ocean of tears to indicate the intensity of sadness, and an ocean of alcohol to indicate the intensity of alcoholic behavior):

(1)Nights upon end of soul searching and an ocean of tears led me to question who I was […]

(2)It's no way to live -- you miss out on a lot and neglect yourself spectacularly when you live in an ocean of alcohol […]

Ocean also sometimes appears in the context of describing a large number of abstract notions as well (an ocean of math concepts, an ocean of lies).

The second major subgroup of English “water” quantifiers consists of words that denote moving water in its liquid state (wave, stream, flood, spate) and in snow or ice form moving in a downward motion (flurry and avalanche). The words wave and spate (a term for a sudden river flood) are predominantly used as quantifiers of abstract notions. Apart from the frequent expression wave of heat, the quantifier wave is often used to describe a lengthy or powerful onset of human emotion (see examples 5, 6), as well as numerous (usually quite negative) actions and events of a similar manner or nature (illustrated by examples 7 and 8). However, as seen in (9), in rare cases wave also appears as a quantifier for a multitude for people, typically upon their arrival or departure from a particular place.

(5)I recall sitting in an office, sweat running down my back, when a wave of panic hit me again. What if I'm not up to the task I've taken on?

(6)Another Brooklyn band currently creating a wave of excitement are Eastern Hollows.

(7)Over a year ago, the regime in Sudan led by Omar al-Bashir, unleashed a wave of violence on its own people […].

(8)The last wave of bank failures came on December 18 with seven banks shutting down for business […].

(9)[…] his family settled in Durham, North Carolina in 2000, just as a wave of Latinos immigrated to the state.

As a quantifier, spate is quite similar to wave, as it is also used primarily when describing a great number of occurrences of a particular action or event, which are typically negative, as exemplified below:

(10)Air traffic controllers in China also err on the side of caution, the result of strict regulations imposed after a spate of accidents in the early 1990s.

(11) However, there were signs of radicalisation among a section of the Tamil Nadu population in response to the war, most notably a spate of self-immolations mentioned earlier.

Stream and flood are also often seen quantifying abstract notions (typically related to forms of information or acts of speech, as in examples 16 and 17), but also occur in quantifying constructions with nouns denoting physical objects (ex. 12, 13) and people (ex. 14, 15). It can be seen from the examples below that when used as a quantifier of multitude, both stream and flood still preserve the “movement” component of their initial meaning. There is also a term stream of consciousness that exists in psychology (introduced by William James in Principles of Psychology (1890)) that denotes a person's thinking process, the thoughts and conscious internal reactions, that are perceived as a continuous flow (much like the flow of water in a stream). In the literary arts, that term stands for a narration method that uses the flow of thoughts in characters' minds to describe the events happening in a story, and both terms also seem to retain the aspect of motion, i.e. the non-stop unbroken influx of thoughts.

(12) The goal is full-body ballistic protection, theoretically allowing the wearer to literally walk through a stream of bullets.

(13)Tail whooped and a hundred warriors shot a flood of arrows into the soldiers at the wagon guns.

(14)Time and diligence turned a trickle of curious visitors to a stream of customers for a growing commercial garden of twenty eight ponds.

(15)Since the 1980s a flood of artists […] began to move into Williamsburg for cheap rent and convenient transportation.

(16)Nonetheless, the stalker has procured this private protected email address and he is bombing away with a stream of emails.

(17)The sentence struck me immediately, and instantly sparked a flood of questions in my brain.

The final two quantifiers in the “water” group are flurry and avalanche.Flurry has been used to denote a sudden rush of strong wind that may also bring about rain, snow and sleet, while avalanche is used to describe the descent of a snow and ice mass down a mountain slope, later also including the fall of rocks and landslides. Both words have broadened their scope of quantifiable entities, namely through the use with other physical objects (as seen in ex.18), but much more often with abstract notions (usually actions or events), as illustrated in examples 19-22. Both quantifiers are used to describe a multitude of a particular activity or occurrences, sometimes accentuating on the sudden appearance of such (as seen in 19, 21), which shows that flurry and avalanche continue to preserve the meaning component related to movement.

(18)If you haven't closed the curtains in a while, get ready for an avalanche of dust when you do.

(19)The attacks on senior authority figures increased the desire for 'results' and consequently brought an avalanche of police raids.

(20) But as the broken bodies were being picked up off the streets of Boston, all we got was an avalanche of excuses as to why it was unreasonable to expect the government to pick these two terrorists off the "watch list.”

(21) Richard's post on accessibility kicked off a flurry of discussion on Saturday morning.

(22)Boma's port is a flurry of activity, filled with ships carrying all manner of wares.

In summary of our overview of the English “water” quantifiers, it's noteworthy that these words have significantly widened their scope of available context. In modern language use most of them are primarily seen as quantifiers of a large number of events or activities, appearing also to describe a multitude of physical objects. Additionally, the corpus data shows that the group of words that initially describe a movement of a large mass of snow or water continue to preserve the aspect of movement when quantifying events or physical objects: the events are either continuously happening (sometimes after suddenly beginning to do so) or otherwise occurring in a multitude of instances. And in the case of physical objects, these quantifiers also point to a sudden appearance and mobility of these entities.

The next group of quantifiers that will be addressed (and presented in Table 7) comprises of words that have been widely used to denote a multitude of particular physical objects. This group is also divided in two subgroups, the first of which unites the quantifiers fleet, arsenal, pile, and stack.

These words all point to multitudes of independent units of a particular kind, while the second subgroup (assembled by bundle, chain, string, and web) indicate that the physical elements that make up the multitude are physically bound or connected amongst each other (a string of pearls, a chain of valves, a web of fibers, a bundle of herbs).

Let's observe the members of the first mentioned subgroup of “physical object” quantifiers, starting with fleet. This word has existed in Old English to indicate ships, rafts, and floating vessels in general, and later shifted to also denote naval force, a group of ships united under one command, the eventually came to mean the naval forces, which remains in use today. As a lexical quantifier it was also used for multitudes of non-military vessels (a fleet of merchant ships), land vehicles (a fleet of trucks) and aircraft, as shown in (23), as well as large groups of people, typically sharing a particular trait, such as line of work (illustrated by ex. 24).

(23) International SOS has been helping travelers stay healthy, safe and secure. Its worldwide reach cannot be matched and includes clinics, alarm centers and a fleet of air ambulances.

(24)As the composer famously said to Sibelius, “The symphony must be like the world, it must contain everything.” For this, Mahler needed a fleet of musicians.

Pile is another member of this cluster of quantifiers, and is attested to be in use to indicate a multitude objects gathered into a heap-like mass from mid-XV century. The corpus data gathered to analyze its modern use show that pile is still mostly present in contexts describing a multitude of countable physical objects (see ex. 25). However, it does occasionally appear with abstract elements, virtually “stacked” into one pile due to the similar nature of each individual element (e.g. 26, 27). In both the latter and former, it's not rare to see a negative connotation brought on by the choice of this particular quantifier.

(25)Pat Lohmann at the New Mexico Daily Lobo is reporting that students at the University of New Mexico (UNM) created a "textbook graveyard," which consisted of a pile of textbooks that UNM's bookstore would not buy back.

(26) Admit it-I'm definitely not the only one here who's gotten lost down the Pinterest rabbit hole a few times. Or been buried under a pile of emails so deep you can't even find the bottom.

(27) First and foremost is that somehow I will screw up in some way that will take a good, potentially marketable debut novel and bury it under a pile of mistakes in execution.

Arsenal and stack are also primarily used as multitude quantifiers for tangible items. First used to indicate a dock with naval stores, arsenal went on to act a quantifier for physical objects (as seen in 29), and also appears in contexts of describing non-tangible concepts, like in (31). In both cases arsenal still seems to retain the aspect of storing something for potential later use. Stack has a similar tendency to be used more often with physical objects (which are placed on top of one another, as in a stack of books, a stack of CDs and in 30), while also being applicable to an accumulation of non-physical items of a similar kind, which may also be visualized and thus described as a stack (32).

(29)This is a very functional, very effectively designed stand that can handle an arsenal of drums with no problem.

(30)What child does not love waking up to a stack of pancakes in the morning? They're tasty and very filling.

(31)It's great and sometimes necessary to have an arsenal of crisis skills, but when you put the right preventative care [...] in place, you should never have to use them.

(32)And as far as Yellowstone is concerned, just two days ago we were cleaning old files and came across a stack of complaints from 2003. From students and their parents desperate that there are as few as 15 [working] hours per week available.

Moving on to the cluster of English quantifiers that hail from initially indicating a multitude of connected physical items, we now turn to bundle. While originally used to quantify a bound collection of things (and later dubbing as a more specific term for a large amount of money), in current use bundle is seen with roughly equal frequency in contexts that depict multitudes of physical (a bundle of scrolls, a bundle of pencils, a bundle of firewood) and non-physical things, as shown in examples 33-35. The widespread phrase bundle of nerves also serves to show how bundle is used to

illustrate the severity or magnitude of nervousness in a particular person.

(33)He was only 25 when he died in 1996, and was such a bundle of contradictions during his brief life that he seemed impossible to fully know.

(34)I've worked with Michelle, now, a number of times. […] She is a bundle of energy and has incredible amounts of enthusiasm for everything she does!

(35)The endangerment finding is both trigger and precedent for sweeping policy changes Congress never approved. America could end up with a bundle of greenhouse gas regulations more costly and intrusive than any climate bill or treaty the Senate has declined to pass or ratify.

Web is another quantifier that hails from terms related to a connected multitude of elements (in Old English it denoted woven fabric and tapestry -- a whole unit created from interconnected fibers, and later gained the familiar meaning for the structure built by spiders). In more modern use, as attested by corpus data, its application as multitude quantifier is often directed towards non-physical elements that form an abstract whole, such as a web of deceit and lies and a web of laws and regulations, as shown in (36) and (37). In this type of context, the intricate structure of fibers in woven fabric and spider webs seems to shift into indicating a multitude that's difficult to navigate and make sense of:

(36)Mike and Rachel race to untangle a web of deceit and lies that stretches two decades into the past.

(37)We are not taxed; we sell services. All of this commercial activity is tightly controlled by a web of laws and regulations, some enforced by various actual governments.

The last two quantifiers in this group are chain and string. Initially denoting a connected series of links of mater or other material, chain later widened its sphere of use to also indicate any series of things that are linked together. This added meaning remains integral in the use of chain as a quantifier of multitude, as it's now often seen as describing a multitude of occurrences or events that take place in relative succession, as shown in (38) and (39). It's worth noting that the term chain as the series of stores or businesses under one brand name, and phrases such as a chain of banks were not considered as examples of chain being used as a lexical quantifier of multitude.