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The subkind reading of nouns & hierarchical structure of kinds

Aviv Schoenfeld, Tel Aviv University

Heinrich Heine University Düsseldorf

January 15th 2020

1/15/2020Aviv Schoenfeld, Tel Aviv University | Heinrich Heine University

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Background

• My PhD thesis, supervised by Fred Landman, is called and is about:

• Reference to subkinds and countability

• The goal is to provide a comprehensive analysis of the most fundamental facts at the interface between these topics.


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Background

• The range of data includes two sorts of indefinite NPs that are built on count and mass nouns and denote sets of kinds.

1. Nouns with a subkind reading

I wonder which bird

cheeseis the most common.

2. NPs with kind

I wonder which kind of bird

cheeseis the most common.


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Overview of talk

• The present topic is concerned with the subkind reading of nouns.

• Research question: Which nouns in English can get a subkind reading?

• Key data: The weapon-weaponry contrast.

• I wonder which weapon

#weaponry is the most common.

• Hypothesis: A noun can get a subkind reading iff it heads a certain hierarchical structure. Contributions:

1. New analysis of why object mass nouns lack a subkind reading.

2. New hypothesized linguistic hierarchical structure of kinds.


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Subkind reading of nouns

• Many nouns, count and mass (animal, wine), can get a subkind (aka taxonomic) reading in addition to an instance reading.

1. Most airlines allow only two animals per flight. instance

2. Spring is associated with two animals: ducks and bunnies. subkind

3. Served chilled, this wine felt cool. instance

4. This wine [Port] gets its name from the city Porto. subkind


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Subkind reading: Animacy

• Nouns with a subkind reading are grammatically inanimate.

1. Toto is a dogwhothat

eats out of the garbage. instance

2. Poodles are a dog#whothat

eats out of the garbage. subkind


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Subkind reading: Countability

• Mass nouns with a subkind reading are grammatically countable.

• In the countability literature, what shifts the interpretation of nouns to the subkind reading is termed the universal sorter (Bunt 1985:11).

1. This is best illustrated with a cheese like Gouda. sg

2. This pizza featured two cheeses: Ricotta and Parmesan. pl


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Subkind reading: Abstract nouns

• Abstract nouns can also get a subkind reading.• Carlson (1980:298), Gillon (1999:57), Grimm (2016:13)

1. Grief is a widespread emotion in the animal kingdom.

2. Thrift is a widespread virtue in such a country.

3. ID theft continues to be a widespread crime.


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Subkind reading: Ambiguity

• With no disambiguating linguistic context, only the non-linguistic one can disambiguate between the instance and subkind readings.

• Two YouTube video titles with smart bird:

1. Can You Do This? - Smart Bird• specimen: Einstein the African Grey Parrot

2. That’s One Smart Bird• subkind: the kea species


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Subkind reading of nouns: Research question

• Seven nouns were mentioned that can get a subkind reading.• animal, bird, cheese, wine, emotion, virtue, crime

• Pre-question: Can all nouns get a subkind reading?1. Carlson (1980:205, 298): Not all nouns in English.

2. Doetjes (1997:§2.1.2): Not all mass nouns in Dutch.

3. Cowper & Hall (2012:29-30): furniture cannot.

4. Rothstein (2017:§4.6): Pluralized object mass nouns cannot.• furniture, jewelry, mail, weaponry



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Key data





• In minimal pairs of count and object mass nouns, the count but not mass noun can get a subkind reading.

• To my knowledge, Sutton & Filip (2018) are the first to notice and analyze this; their example is vehicle-transport (ex.5).


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Experiment: Task

• To support the judgments of the weapon-weaponry contrast, I ran an experiment with a word preference task.

1. Lefthand word is much better than righthand one in blank space.

3. Both options are equally as good/bad.

5. The righthand word is much better.


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Experiment: Factor

• The experiment had one factor, the linguistic context of the blank space, with four levels.

prediction

1. subkind I wonder which _ is the most common. 1

2. count You can choose between several nearby _. 1

3. cumulative On our way back, we saw some interesting _. 3

4. mass A bit of _ can make a big difference. 5


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Experiment: Minimal pairs

• The tasks were based on 12 (near-)minimal pairs of count and object mass nouns (Wisniewski, Imai & Casey 1996, Casey 1997).

9. confection-confectionery5. plant-vegetation1. wild animal-wildlife

10. suitcase-luggage6. vegetable-produce2. sea animal-sealife

11. shoe-footwear7. machine-machinery3. farm animal-livestock

12. hat-headgear8. weapon-weaponry4. farm bird-poultry


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Experiment: Details

• 12 pairs of nouns × 4 linguistic contexts = 48 word preference tasks.

• They were divided in 4 lists with no fillers, so 12 tasks in each list.

• The survey was made in Google forms.

• The order of the tasks was randomized via Shuffle question order.

• 88 self-reported native monolingual English speakers, 22 for each list.

• Most were recruited via the SampleSize subreddit (Shatz 2017).


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Experiment: Results

• All pairwise comparisons are statistically significant, except subkind-count.

• The weapon-weaponry contrast is experimentally supported.


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1.90 1.77

2.87

4.46

1.00

2.00

3.00

4.00

5.00

subkind count cumulative mass

Previous accounts

• Next, I review two relevant previous accounts.

1. Grimm & Levin (2017): Object mass nouns lack a subkind reading.

2. Sutton & Filip (2018): The weapon-weaponry contrast.


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Grimm & Levin (2017)

• Grimm & Levin (2017): Pluralized object mass nouns (e.g. mails) lack a subkind reading.• #Letters and packages are two mails that I like. (cf. ex.8b)

• Account: The extensions of nouns that name would-be kinds of mail are not necessarily subsets of the extension of mail.• Not every letter is mail (e.g. a letter on display in a museum).


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Grimm & Levin (2017:ex.14)


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Grimm & Levin (2017): Challenge

1. The subkind relation can hold without subset holding.• Knives are a prominent weapon in ancient Indian history.

• Not every knife is a weapon (e.g. a disposable plastic knife).

2. The subkind relation can fail even when subset holds.

• Starfish are a sea animal

#sealifewith spiny skin.

• Every starfish counts as sealife.

• In sum, subkind and subset are logically independent.


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• Nouns with a subkind reading can have kinds in their denotation that are named by nouns whose extensions are not necessarily subsets of the extension of the noun with a subkind reading.

1. Knives are a prominent weapon in ancient Indian history.

2. Birds are a popular pet because they're small.

3. Finches are a pet that won't get on the neighbors’ nerves.

4. Buckets are a toy that we often think of in relation to beaches.


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• Nouns with a subkind reading can have kinds in their denotation that are named by nouns whose extensions are not necessarily subsets of the extension of the noun with a subkind reading.

5. Cherry tomatoes are a snack that's seasonal for many people.

6. Scallops are a popular seafood around the world.

7. Thrift is a widespread virtue in such a country.

8. Grass is the most valuable plant on the planet.


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• The pair grass-plant exemplifies a larger pattern.

1. If the superordinate kind is named by a count noun N1, (e.g. plant)

2. and the subkind is named by a mass noun N2, (e.g. grass)

3. then the extension of N2 is not necessarily a subset of that of N1.

• Artillery is a weapon with two major roles.

• Two rockets are artillery, but not a weapon (they are two weapons).


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• I see no obvious extension of Grimm & Levin’s analysis to account for the weapon-weaponry contrast.



• How they would explain weaponry lacking a subkind reading:

• The extensions of nouns that name would-be kinds of weaponry are not necessarily subsets of the extension of weaponry.• Not every knife is weaponry (e.g. a disposable plastic knife).


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• I see no obvious extension of Grimm & Levin’s analysis to account for the weapon-weaponry contrast.



• However, weapon with a subkind reading can have the knife kind in its denotation, contra what they seemingly predict.• Knives are a prominent weapon in ancient Indian history.


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Sutton & Filip (2018)

• Sutton & Filip (2018): Pluralized object mass nouns (e.g. furnitures, transports) lack a subkind reading, but their count counterparts (if they exist, e.g. vehicles) can get it (ex.4b, 5).

1. #I ordered two furnitures from Ikea: chairs and tables.

2. The brief […] is to produce four vehicles

#transportsranging in size from

the Ford Fiesta to the Vuaxhall Cavalier.


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• In Sutton & Filip’s (2016a, 2016b) framework of countability, the denotations of count and mass nouns differ as follows.

1. Count: has built-in a mechanism for overlap resolution.

2. Mass: does not; denotations are potentially overlapping sets.

• Nominals are countable iff their set denotation is disjoint.


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(p.1209, fig.6)

vanity

Aviv Schoenfeld, Tel Aviv University | Heinrich Heine University Düsseldorf | January 15th 2020


• Sutton & Filip: furnitures lacks a subkind reading because would-be subkinds in the same level of categorization overlap.

• e.g. vanities overlap with chairs, tables and mirrors.


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Sutton & Filip (2018): fig.6


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• For why weaponry lacks a subkind reading, Sutton & Filip would appeal to an example parallel to vanities and mirrors.

• e.g. pistol swords overlap with knives and guns.

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pistol sword

Aviv Schoenfeld, Tel Aviv University | Heinrich Heine University Düsseldorf

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• Sutton & Filip (2018): Being a count noun, the denotation of weaponwith a subkind reading has a mechanism for overlap resolution.

• Thus, weapon with a subkind reading denotes a set of disjoint kinds.• The overlap between pistol swords, guns and knives is resolved.

• Thus, weapon can get a subkind reading.


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Sutton & Filip (2018): Challenge

• Sutton & Filip’s analysis is challenged by natural object mass nouns.• wildlife, sealife, livestock, poultry, vegetation, produce

• In my experiment, they were judged as worse than their count counterparts in a context that induces the subkind reading.

• I wonder which wild animal

#wildlifeis the most common.

• However, kinds of wild animals in the same level of categorization do not overlap in the same way as vanities and mirrors.


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Hypothesis: Hierarchical structure of kinds

• Grimm & Levin, Sutton & Filip: A noun can get a subkind reading iff it heads a certain hierarchical structure.

1. Grimm & Levin: One where subkinds are necessarily subsets of the superordinate kind.• aka taxonomy. In the narrow sense, a structure of bio-classification.

• Kay (1971, 1975), Cruse (1986:§6), Murphy (2002:§7)

2. Sutton & Filip: One where subkinds in the same level of categorization are (mereologically) disjoint.• In Kay (1971), kinds in the same level are set-theoretically disjoint.


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Hypothesis: Hierarchical structure of kinds

• Grimm & Levin, Sutton & Filip: A noun can get a subkind reading iff it heads a certain hierarchical structure.

• Me: The relevant structure is akin to Kay’s (1971) taxonomy, but with two changes, motivated by linguistic data regarding which kinds can be in the denotation of nouns with a subkind reading.

• Next, I present Kay’s (1971) definition of a taxonomy.


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Kay’s (1971) taxonomy: Taxonomic structure

• A structure τ = <𝒦,⊃> is a taxonomic structure iff

• 𝒦 is a non-null set of non-null sets (the set of kinds)

• ⊃ is the relation of strict subset restricted to 𝒦

1. There is a unique member of 𝒦 that is a strict superset of all other members of 𝒦 (the head of the structure)

2. ∀J∊𝒦, the set of sets in 𝒦 that are immediate strict subsets of J is null or partitions J


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Kay’s (1971) taxonomy: Partition

• Let X be a set and 𝒵 a set of sets. 𝒵 partitions X iff

1. 𝒵 is a non-null set of non-null subsets of X• 𝒵⊆ {Y : Y⊆X} and {} ∉ 𝒵 and 𝒵 ≠ {}

2. Every element of X is in an element of 𝒵• For every α∈X there’s a Y∈𝒵 such that α∈Y

3. No element of X is in two elements of 𝒵• For every Y1,Y2∈𝒵, if Y1≠Y2 then there’s no α s.t. α∈Y1 and α∈Y2


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Kay’s (1971) taxonomy: Taxonomic structure

• τ1 = <𝒦1,⊃1>

• 𝒦1 =

{🐧,🦆,🦅,🦉},

{🐧,🦆}, {🦅,🦉},

{🐧}, {🦆}, {🦅}, {🦉}

• ⊃1 = <{🐧,🦆,🦅,🦉},{🐧,🦆}>, <{🐧,🦆,🦅,🦉},{🦅,🦉}>,

<{🐧,🦆,🦅,🦉},{🐧}>, <{🐧,🦆,🦅,🦉},{🦆}>, <{🐧,🦆,🦅,🦉},{🦅}>, <{🐧,🦆,🦅,🦉},{🦉}>,

<{🐧,🦆},{🦆}>, <{🐧,🦆},{🐧}>, <{🦅,🦉},{🦅}>, <{🦅,🦉},{🦉}>

{🐧,🦆,🦅,🦉}

{🐧,🦆} {🦅,🦉}

{🐧} {🦆} {🦅} {🦉}


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Kay’s (1971) taxonomy

• To upgrade a taxonomic structure to a taxonomy, add

1. N the set of names

2. R R ⊆ N×𝒦, the naming relation, from names to kinds

• <𝒦,⊃> taxonomic structure

• <𝒦,N,⊃,R> taxonomy


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Kay’s (1971) taxonomy

Taxonomic structure τ1 is embedded in taxonomy τ1=<𝒦1,N1,⊃1,R1>

• N1 = bird,

waterfowl, raptor, bird of prey,penguin, duck, eagle, owl

• R1 = <bird,{🐧,🦆,🦅,🦉}>,

<waterfowl,{🐧,🦆}>, <raptor,{🦅,🦉}>, <bird of prey,{🦅,🦉}>,

<penguin,{🐧}>, <duck,{🦆}>, <eagle,{🦅}>, <owl,{🦉}>


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Kay’s (1971) taxonomy: Example

• Tree visual representation of taxonomy τ1

• raptor and bird of prey are synonyms.

R1(bird) = {🐧,🦆,🦅,🦉}

R1(waterfowl) = {🐧,🦆} R1(raptor) = R1(bird of prey) = {🦅,🦉}

R1(penguin) = {🐧} R1(duck) = {🦆} R1(eagle) = {🦅} R1(owl) = {🦉}


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Kay’s (1971) taxonomy: Challenge

• Kay’s (1971) taxonomy cannot accommodate kinds named by massnouns, assuming they are cumulative sets (Link 1983:130).

1. ⟦weapon⟧ = {🔪1,🔪2,🔫} count

2. ⟦weaponry⟧ =

🔪1⊔🔪2⊔🔫,

🔪1⊔🔪2, 🔪1⊔🔫, 🔪2⊔🔫,

🔪1, 🔪2, 🔫

mass


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• Say the cheese is a piece of mozzarella 🧀m and cheddar 🧀c.

• 𝒦3=

🧀c⊔🧀m,

🧀c, 🧀m,

🧀c , 🧀m

N3 = cheese,

cheddar, mozzarella

• R3 = <cheese,

🧀c⊔🧀m,

🧀c, 🧀m>,

<cheddar, 🧀c >, <mozzarella, 🧀m >


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• <𝒦3,N3,⊃3,R3> is not a taxonomy under Kay’s (1971) definition.

• The kind named cheese is not partitioned by the set of its immediate strict subsets in 𝒦3.

•🧀m⊔🧀c is in no member of {{🧀m},{🧀c}}.

R1(cheese)=🧀c⊔🧀m,

🧀c, 🧀m

R1(mozzarella)={🧀m}R1(cheddar)={🧀c}


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Unclassified specimens

• Intuitively, the set of subkinds should partition not the entire set of cheese, but the set minus elements like 🧀m⊔🧀c.

1. That is an unclassified specimen: cheese unclassified for variety.

2. Another example: a mutt, a dog that is unclassified for breed.

• Unclassified specimens may prevent partition from holding in Kay’s (1971) taxonomy.

• To handle unclassified specimens, I add to the structure ways of classification, which may correspond to words like species, breed.


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Ways of classification: Intuitively

• Intuitively, a way of classification allows one to distinguish between entities that are and are not classified according to that way.

1. Breed allows one to distinguish between dogs that are and are not classified for breed, i.e. purebreds and mutts respectively.

2. Variety allows one to distinguish between sums of cheese that are and are not of a variety. Examples of the latter:1. A sum of cheese of multiple varieties (e.g. 🧀m⊔🧀c).

2. Say I start following a recipe for cheddar, but I change things about it such that the resulting cheese is not cheddar, nor of any other variety.


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Ways of classification: Formally

• I formalize ways of classification as functions from sets to the subset whose members are classified according to the relevant way.

• 𝕔var is the way of classification that corresponds to variety.

1. 𝕔var(🧀c⊔🧀m,

🧀c, 🧀m) = {🧀m,🧀c}

• the set of sums of cheese that are classified for variety

2. ¬𝕔var(🧀c⊔🧀m,

🧀c, 🧀m) = {🧀m⊔🧀c}

• the set of sums of cheese that are unclassified for variety


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𝕔-taxonomic structure

• The 𝕔-taxonomic structure has two additional components.

1. ℂ the set of ways of classification

2. f function from L (levels of the structure) to ℂ• each level except the lowest one is associated with a different 𝕔∈ℂ

• <𝒦,⊃> taxonomic structure (Kay 1971)

• <𝒦,ℂ,⊃,f> 𝕔-taxonomic structure


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• The 𝕔-taxonomic structure is defined so that sets of unclassified specimens are themselves members of 𝒦.

• This is empirically motivated by the fact that the mutt kind can be in the denotation of dog with a subkind reading, along with dog breeds.

1. German shepherds are a medium sized dog.

2. Mutts are the most popular dog in America.


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1. Kay’s (1971) taxonomic structure• Unclassified specimens may prevent partition from holding.

2. 𝕔-taxonomic structure• Sets of unclassified specimens are themselves kinds; partition holds.

𝕔-taxonomic structureNot taxonomic structure

R1(cheese)=🧀c⊔🧀m,

🧀c, 🧀mR1(cheese)=

🧀c⊔🧀m,

🧀c, 🧀m

R1(mozzarella)={🧀m}{🧀c⊔🧀m}R1(cheddar)={🧀c}R1(mozzarella)={🧀m}R1(cheddar)={🧀c}


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• To demonstrate the expressive range of the 𝕔-taxonomic structure,

• I present one of cars with two ways of classification, corresponding to series and model.

1. s1m1 belongs to series 1 and is of model 1

2. s1m𝘟 belongs to series 1 and is unclassified for model

3. s𝘟m5 is unclassified for series and is of model 5


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• 3 of the 11 sets in this structure are of unclassified specimens.1. {s𝘟m5, s𝘟m𝘟} cars that are unclassified for series

2. {s1m𝘟} cars of series 1 that are unclassified for model

3. {s𝘟m𝘟} cars that are unclassified for series and model

{s1m1, s1m2, s1m𝘟, s2m3, s2m4, s𝘟m5, s𝘟m𝘟}

series {s1m1, s1m2, s1m𝘟} {s2m3, s2m4} {s𝘟m5, s𝘟m𝘟}

model {s1m1} {s1m2} {s1m𝘟} {s2m3} {s2m4} {s𝘟m5} {s𝘟m𝘟}


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Subkinds need not be subsets

• Recall: Nouns with a subkind reading can have kinds in their denotation named by nouns whose extensions are not necessarily subsets of the extension of the noun with a subkind reading.

1. Knives are a prominent weapon in ancient Indian history.


• This indicates that the relation in the linguistic hierarchical structure of kind is not strict subset.

• Thus, I replace strict subset with spreading over, defined next.


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Spreading over: Definition

• Let X be a set and 𝒵 a set of sets. 𝒵 spreads over X (Xᕈ𝒵) iff

1. Every element of X is in an element of 𝒵.• For every α∈X there’s a Y∈𝒵 such that α∈Y

2. Every element of 𝒵 has an element that is in X.• For every Y∈𝒵 there’s a α∈X such that α∈Y

3. No element of X is in two elements of 𝒵.• For every Y1,Y2∈𝒵, if Y1≠Y2 then there’s no α s.t. α∈Y1 and α∈Y2

• I am unsure whether a disjointedness condition is needed, and whether it should be set-theoretic (Kay 1971) or mereological (Sutton & Filip 2018).


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Spreading over

• X (an extension of weapon) is spread over by 𝒵, with extensions of knife and artillery, despite them not being subsets of X.

1. ⟦knife⟧ includes 🍴, a non-weapon plastic knife.

2. ⟦artillery⟧ includes 🚀1⊔🚀2, a sum of 2 rockets.

⟦weapon⟧ = {🔪,🚀1,🚀2}X =

⟦artillery⟧ = 🚀1⊔🚀2,

🚀1, 🚀2

}{⟦knife⟧ = {🍴,🔪},𝒵 =


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Spreading over: Comparison to subset

• The crucial difference between subset and spreading over.

1. ⟦pet⟧ ⊇ ⟦dog⟧ every element of ⟦dog⟧ is in ⟦pet⟧

2. ⟦pet⟧ ᕈ {⟦dog⟧, ⟦cat⟧} every element of ⟦pet⟧ is in ⟦dog⟧ or ⟦cat⟧

• Crucially, ⟦dog⟧ and ⟦cat⟧ can have elements that are not in ⟦pet⟧.• Specifically, not-pet (i.e. stray) dogs and cats.


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Spreading over: Comparison to partition

• In spreading over, unlike partition, members of 𝒵 can have elements that are not in X.

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𝒵2 partitions X𝒵1 doesn’t partition X

𝒵2 spreads over X𝒵1 spreads over X

= X{🔪,🚀1,🚀2}{🔪,🚀1,🚀2}X =

= 𝒵2{🚀1,🚀2}}{{🔪},🚀1⊔🚀2,

🚀1, 🚀2

}{{🍴,🔪},𝒵1 =


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Spreading over 𝕔-structure

• The second change to Kay’s (1971) taxonomy, after adding ways of classification, is replacing strict subset with spreading over.

• <𝒦,⊃> taxonomic structure (Kay 1971)

• <𝒦,ℂ,⊃,f> 𝕔-taxonomic structure

• <𝒦,ℂ,ᕈ,f> spreading over 𝕔-structure


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Spreading over 𝕔-structure

• 𝒦4 =

1,2,3 ,

1,2,4 ,

1,6 , 2,4,73,5 ,

• ᕈ4 = < {1,2,3},{{1,2,4},{3,5}}>, < {1,2,3},{{1,6},{2,4,7},{3,5}}>,

< {1,2,4},{{1,6},{2,4,7}}>


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{1,2,3}

{{1,2,4}, {3,5}}

{{1,6}, {2,4,7}}

Kinds as intensions

• In the spreading over 𝕔-structure, as in Kay’s (1971) taxonomic structure, kinds are modelled as sets.

• This is unintuitive (Kay 1975), and makes incorrect predictions.

• Thus, I make 𝒦 (the set of kinds) a set not of sets (<α,t>), but of properties (<s,<α,t>>).

• Correspondingly, I use a relation of spreading over that holds between a property P and set of properties ℛ, defined next.


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Kinds as intensions

• Let P be a property, ℛ a set of properties and S a set of circumstances of evaluation. ℛ spreads over P iff

1. Every element in every extension of P is also in the extension of an element of ℛ in the same circumstance.• For every s∈S and α∈P(s) there is a Q∈ℛ such that α∈Q(s)

2. Every element of ℛ has a circumstance where its extension shares an element with the extension of P in the same circumstance.• For every Q∈ℛ there is a s∈S and α∈P(s) such that α∈Q(s)

3. For every Q1,Q2∈ℛ, if Q1≠Q1 then there’s no α and s∈S s.t.α∈Q1(s) and α∈Q2(s)


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Kinds as intensions

⟦weapon⟧ = s1 → {🔪,🚀1,🚀2}s2 → {}

P =

⟦artillery⟧ = s1 →

🚀1⊔🚀2,

🚀1, 🚀2s2 → {}

}{⟦knife⟧ = s1 → {🍴,🔪}s2 → {}

,ℛ =


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Noun kind structure

• To upgrade a 𝕔-spreading over structure to a noun kind structure (an alternative to Kay’s 1971 taxonomy), add:

1. N1 names of kinds N1 = {bird, eagle…}

2. N2 names of ways of classification N2 = {species, breed…}

3. R1⊆ N

1×𝒦 naming kinds R1 = {<eagle, s1→{🦅}

…>…}

4. R2⊆ N

2×ℂ naming ways of classification R2 = {<species,𝕔spcs>…}


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weapon-weaponry contrast: Assumptions

• My account of the weapon-weaponry contrast relies on assuming:

1. Kinds named by count nouns have disjoint extensions.

2. Kinds named by mass nouns have cumulative extensions.

3. Sums of objects of the same kind are classified. e.g. 🔪1⊔🔪2

4. Sums of objects of different kinds are unclassified. e.g. 🔪1⊔🚀• Like how a sum of cheddar and mozzarella is a sum of cheese that is

unclassified for variety.


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• P is a property, 𝕔 a way of classification and S a set of circumstances.

• 𝕔(P) is the sub-property of P s.t. for every s∈S, 𝕔(P)(s) = 𝕔(P(s))

1. ⟦weaponry⟧ = [s1 →

🔪1⊔🔪2⊔🔫,

🔪1⊔🔪2, 🔪1⊔🔫, 🔪2⊔🔫,

🔪1, 🔪2, 🔫

]

2. 𝕔(⟦weaponry⟧) = [s1 → 🔪1⊔🔪2,

🔪1, 🔪2, 🔫]


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• My account of the weapon-weaponry contrast relies on assuming:

5. Count noun members of N1 (the set of names of kinds) are singular.

• This assumption is derived from a more general one.

6. Members of N1 are lexically-entered nouns.

• This is how I incorporate Carlson’s (1980:206, 298) analysis of which nouns in English can get a subkind reading.

• A noun can get a subkind reading for a speaker only if there are nouns in their lexicon that name its subkinds.• (Too strong, but that’s a separate issue.)


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weapon-weaponry contrast

• A noun can get a subkind reading iff it heads a noun kind structure.

• Noun N in language L heads a noun kind structure iff

1. There is a way of classification 𝕔 such that

2. Property 𝕔(⟦N⟧) is spread over by a set of properties ℛ such that

3. Every Q∈ℛ is named by a lexically-entered noun in language L

• Next, I show that weapon, unlike weaponry, satisfies these.


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• Fact: weapon can get a subkind reading.

• Account: 𝕔(⟦weapon⟧, the property of 𝕔-classified weapons, is spreadover by a set of properties that are named by English nouns, whichcan be count (e.g. knife) or mass (e.g. artillery).

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𝕔(⟦weapon⟧) = [s1 → {🔪,🚀1,🚀2}]P =

⟦artillery⟧ = [s1 →🚀1⊔🚀2,

🚀1, 🚀2

]}{⟦knife⟧ = [s1 → {🍴,🔪}],ℛ =


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• Fact: weaponry cannot get a subkind reading.

• Account: 𝕔(⟦weaponry⟧, the property of 𝕔-classified weaponry, cannot be spread over by a set of properties that are named by English nouns.

• There are not enough mass nouns in English like artillery that name kinds of weapons, e.g. no mass counterpart of knife.


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•🔪1⊔🔪2 prevents P from being spread over by ℛ.

𝕔(⟦weaponry⟧) = [s1 → 🔪1⊔🔪2,

🔪1, 🔪2, 🔫]P =

⟦gun⟧ = [s1 → {🔫}]}{⟦knife⟧ = [s1 → {🍴,🔪1,🔪2}],ℛ =


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• My account of the contrast appeals to cumulative reference.

• How easy it is to spread over (SO) the classified sub-property depends on whether the property has cumulative extensions.

1. Disjoint (named by count noun, e.g. weapon): SO easier• It does not matter whether the properties in the spreading over set ℛ are

named by count or mass nouns.

2. Cumulative (named by mass noun, e.g. weaponry): SO harder• Every property in the spreading over set ℛ must be named by a mass noun.


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cheese-weaponry contrast

1. I wonder which cheese is the most common.

2. #I wonder which weaponry is the most common.

• weaponry: The property of 𝕔-classified weaponry cannot be spread over by a set of properties that are named by English nouns.• There are not enough mass nouns in English like artillery that name kinds of

weaponry, e.g. no mass counterpart of knife.

• cheese: The property of 𝕔-classified cheese is spread over by a set of properties that are named by English nouns.• There are enough mass nouns in English, e.g. cheddar, mozzarella…


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• Main difference between my account and Sutton & Filip’s (2018).

1. Theirs: countability + overlap of would-be subkinds (in same level)

2. Mine: cumulative reference

• Thus, my account is not challenged by natural object mass nouns.

1. wildlife and weaponry both have cumulative extensions.

2. Not all their would-be subkinds are named by English mass nouns.

3. Thus, neither heads a noun kind structure, correctly predicting them to lack a subkind reading.


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Carlson (1980): The subkind reading

• By requiring N1 to include only lexically-entered nouns,

• I incorporate Carlson’s (1980) analysis of which English nouns can get a subkind reading, and the predicted inter-speaker variation.

1. I wonder which animal

?countryis the most common.

2. I wonder which virtue

?courageis the most common. (p.298)

3. I wonder which cheese?dust

is the most common.

• Following Carlson, I attribute the oddness to not knowing names of subkinds, which is subject to inter-speaker variation.


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Conclusion

• The present topic is concerned with the subkind reading of nouns.





• Hypothesis: A noun can get a subkind reading iff it heads a noun kind structure. Contributions:

1. New analysis of why object mass nouns lack a subkind reading.

2. New hypothesized linguistic hierarchical structure of kinds.


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Loose ends

1. How I account for food being able to get a subkind reading.• I wonder which food is the most common.

2. Grimm & Levin and Sutton & Filip analyze the lack of a subkindreading of pluralized object mass nouns (e.g. furnitures).

• I argue that object mass nouns lack a subkind reading altogether.

• My analysis is geared towards that generalization.


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Future research: The subkind relation

• I will formulate a new definition of the subkind relation.

• Different than those in Carlson (1980:206, 212), Cruse (1986:§6) and Krifka et al. (1995:§1.3.3), which

• model subkinds in a way that is equivalent to them being subsets of the superordinate kind in every circumstance.

• This incorrectly predicts the following to be infelicitous.1. Knives are a prominent weapon in ancient Indian history.



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Future research: The subkind relation

1. What is the appropriate notion of disjointedness of kinds?1. #Birds are a kind of pet, and so are parrots.

2. Carlson (1980:212): Collies and watchdogs can’t count as two kinds of dogs.

3. Sutton & Filip (2018): Mereological overlap of vanities, mirrors is relevant.

2. Should the subkind relation be reflexive?• The analyses of Carlson (1980:276), Zamparelli (1998:283) and Dayal

(2004:426) of definite generics rely on it being reflexive.

3. Which properties can participate in the subkind relation?

•Israeli semanticists

#Semanticists in Israelare a kind of linguist.


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Any questions?Aviv Schoenfeld, Tel Aviv University

Heinrich Heine University Düsseldorf

January 15th 2020


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Subkind reading of food

• If every classified sum of food has a mass noun (besides food) with it in its extension, then I correctly predict food to get a subkind reading.• I wonder which food is the most common.

• Apparent counter-example: 🥪 (a sandwich)

• It follows from assumption 4 on slide 63 that 🥪 is unclassified.

4. Sums of objects of different kinds are unclassified. (e.g. 🔪1⊔🚀)

• Before determining whether my analysis needs revision, I should consider more apparent counter-examples.


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The subkind reading: Mass occurrences

• I argue: The operation that shifts the interpretation of nouns to the subkind reading makes the noun countable.

• Correlate: Mass occurrences of nouns cannot get a subkind reading.

• Apparent counter-examples: more N, different N


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1. Which store offers more cheese?• Intuitive paraphrase: Which store offers a greater variety of cheese?

2. Who has more furniture?• Has a reading that coincides with asking who has more kinds.

• McCawley (1975:ex.14-15), Grimm & Levin (2012), Gafni & Rothstein (2014)

• Potential sources of this reading.

1. The noun (cheese, furniture) got a subkind reading.

2. more introduces a parameter that can be made overt via an in terms of clause (e.g. more in terms of variety).


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1. I found that different cheese had different melting properties.• Intuitive paraphrase: different kinds of cheese

2. Different rooms have different furniture for different purposes.• Intuitive paraphrase: different kinds of furniture

• Potential sources of intuitive paraphrases.

1. The noun (cheese, furniture) got a subkind reading (Alrenga 2007).

2. different introduces a parameter that can be made overt via an in terms of clause (e.g. different in terms of type).


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• If mass occurrences could get a subkind reading, it should happen generally, not just with more and different. This is not borne out.

1.Many cheeses are⇎Much cheese is

loved by children.

2.Many wild animals are⇎Much wildlife is

loved by children.

• More examples on next two slides.

• Thus, the reading that coincides with the subkind reading with moreand different does not come from the noun getting a subkind reading.


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1.Many cheeses are⇎Much cheese is

loved by children.

2.Few cheeses sustain

⇎Little cheese sustainsthis country’s economy.

3. A number of cheeses sustain⇎bit of cheese sustains

this country’s economy.

4. Mostcheeses are#cheese is

abundant.

5. Allcheeses have⇎cheese has

a name.


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1.Many wild animals are⇎Much wildlife is

loved by children.

2.Few wild animals sustain⇎Little wildlife sustains

this country’s economy.

3. A number of wild animals sustain

⇎bit ofwildlife sustainsthis country’s economy.

4. Mostwild animals are

#wildlife isnumerous.

5. Allwild animals were⇎wildlife was

named in the garden of Eden.


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Sherlock’s encyclopedic knowledge of muds

• A big draw of the Sherlock Holmes stories was Holmes's ability to make huge logical leaps that depended only on his powers of observation and encyclopedic knowledge of different muds, tobacco varieties, and everything else.

• The above muds with a subkind reading is felicitous to me, despite not heading a noun kind structure for me.• I do not know of a way of classification that distinguishes between classified

and unclassified mud.

• The felicity could be aided by the ease of accommodating that Sherlock knows such a way of classification.


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Experiment: Results


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subkind count cumulative mass1 wild animal wildlife 1.32 1.73 4.14 4.622 sea animal sealife 1.76 1.41 2.95 4.503 farm animal livestock 2.23 2.57 2.14 4.684 farm bird poultry 2.36 3.14 3.52 4.595 plant vegetation 1.41 1.09 2.27 4.386 vegetable produce 1.81 1.36 2.45 4.057 machine machinery 2.05 2.00 3.32 4.828 weapon weaponry 1.27 1.41 3.14 4.599 confection confectionery 2.86 2.14 3.05 3.8610 suitcase luggage 2.10 1.32 3.36 4.6411 shoe footwear 2.14 1.76 2.00 4.2312 hat headgear 1.55 1.41 2.10 4.55

Levels of categorization

1. We focused on the most populous animal from each category: birdsfor small animals and baboons for large animals.

2. There are only two mammals–one species and one genus–that can't instinctively swim [giraffes and apes].

3. Certain kinds of birds -- most obviously pigeons and house sparrows, but also, surprisingly, raptors and waterfowl as well --actually thrive in urban areas.

less abstract more abstract

Aviv Schoenfeld, Tel Aviv University | University of Konstanz, November 5th 2019


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References

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