The$Radial$Categoryasan$ Emergent$Structure - UiT

The Radial Category as an Emergent Structure

Hanne M. Eckhoff, Laura A. Janda, and Tore Nesset

Overview

PART ONE: How Do We Know the Structure of a Radial Category?

PART TWO: A Radial Category Emerges from our Data

PART THREE: Why LinguisJc Categories Should be CogniJvely RealisJc

1. APART SP (38) raz-‐pilit’ ‘saw apart’ NP (22) raz-‐gryzt’ ‘gnaw apart’

6. EXCITEMENT SP (29) raz-‐kalit’ ‘make red-‐hot’ NP (16) raz-‐gorjačit’ ‘heat up, irritate’

4. SWELL SP (3) raz-‐dut’ ‘inMlate’ NP (9) raz-‐puxnut’ ‘swell’

3. SPREAD SP (30) raz-‐katat’ ‘roll out’ NP (17) raz-‐vetvit’sja ‘branch out’

2. CRUSH SP (7) raz-‐toptat’ ‘trample’ NP (5) raz-‐davit’ ‘crush’

7. UN-‐ SP (38) raz-‐gruzit’ ‘unload’

5. SOFTEN / DISSOLVE SP (7) raz-‐tvorit’sja ‘dissolve’ NP (6) raz-‐tajat’ ‘melt’

Russian RAZ-‐: a Radial Category

PART ONE: How Do We Know the Structure of a Radial Category?

•  A radial category is made up of: –  nodes, one (or more) of which is a

protototype –  arrangement of nodes

•  How do we know what the nodes are? –  Nodes can exist on various levels of

abstracJon •  How do we idenJfy the prototype?

–  Various criteria can point to different candidates

•  How do we find the arrangement?

•  Linguists have oSen relied on their intui?on (aka experJse, logic) to idenJfy the nodes, prototype, and arrangment of a radial category

•  There are some criteria (Taylor 1995, Lewandowska-‐Tomaszczyk 2007), but is this enough?

In our study, the nodes, prototype, and arrangement emerge from the data...

... but they also need our help!

PART TWO: Our Data The verb BYTI ‘be’ in Old Church Slavonic

•  Old Church Slavonic is the first literary language of the Slavs, preserved in a collecJon of texts from the 9th-‐11th centuries CE

•  Our data is 2,428 aêstaJons of the verb BYTI ‘be’ extracted from the PROIEL corpus h^p://foni.uio.no:3000

•  All our data is publicly available at TROLLing: hdl:10037.1/10074

Controversy: Is BYTI ‘be’ one verb or two?

Morphological subparadigm

es-‐forms bū-‐forms

“duplicate” forms for es-‐group and bū-‐group

present jestъ bǫdetъ

imperfect běaše *bǫdeaše

aorist bě by(stъ)

present parJciple sǫšt-‐ bǫdǫšt-‐

unique forms subjuncJve bi —

“shared” forms (bū) past parJciple byvъ

imperaJve bǫdi

infiniJve by8

l-‐form bylъ

Two hypotheses

H2: BYTI ‘be’ is a pair of verbs This is a null hypothesis ∴ We do NOT expect a single coherent radial category

We test the hypotheses by means of: Construc?onal profiling -‐-‐ relaJve frequency of construcJons Gramma?cal profiling -‐-‐ relaJve frequency of grammaJcal forms

H1: BYTI ‘be’ is a single verb But it is clearly complex, polysemous ∴ We expect a single coherent radial category

Two hypotheses

H2: BYTI ‘be’ is a pair of verbs This is a null hypothesis ∴ We do NOT expect a single coherent radial category

We test the hypotheses by means of: Construc?onal profiling -‐-‐ relaJve frequency of construcJons Gramma?cal profiling -‐-‐ relaJve frequency of grammaJcal forms

H1: BYTI ‘be’ is a single verb But it is clearly complex, polysemous ∴ We expect a single coherent radial category

The en?re radial category of BYTI

emerges objec?vely from the data

Two steps: nodes and arrangement

STEP ONE: ConstrucJonal profile of BYTI –  RelaJve frequency distribuJon of construcJons that BYTI appears in

–  ConstrucJons ≈ meanings of BYTI –  Emerges from corpus annotaJon data –  This gives us the nodes of the radial category

STEP TWO: GrammaJcal profiles of the BYTI construcJons –  RelaJve frequency distribuJon of es-‐ and bū-‐forms for each construcJon

–  Emerges from corpus annotaJon data –  This gives us the arrangement of the radial category

Construc?onal profiling of BYTI

•  Aggregated informaJon from annota?on in PROIEL corpus, including: –  syntacJc funcJon (auxiliary, matrix verb, dependent verb) –  argument structure (oblique arguments, predicaJve complements & adverbials, part of speech and case marking of arguments)

•  Hand sor?ng to separate personal from impersonal and group construcJons according to similar paêrns

•  Yields ten construc?ons ≈ meanings of BYTI

Ten constructions ≈ meanings of BYTI (first five)

aux: auxiliary in perfect tense pravě sǫdilъ esi ‘you have judged rightly’ (Mar. Luke 7:43)

auxiliaroid: used with parJciples pisano estъ ‘it is wriên’ (Mar. Ma^. 21:13)

copula: vy este solь zemi ‘you are the salt of the earth’ (Zogr. Ma^. 5:13)

copular benefac?ve: with a daJve nominal uněe estъ vamъ da azъ idǫ ‘(it) is beêr for you that I should go’ (Mar.

John 16:7)

copular impersonal: lacks referenJal subject bě že noštъ ‘(it) was night’ (Mar. John 13:30)

Ten constructions ≈ meanings of BYTI (remaining five)

copular possessive: with daJve nominal possessor kako emu estъ synъ ‘how can he be his son?’ (Mar. Luke 20:44)

existen?al: with referenJal subject vъ domu otca moego obitěli mъnogy sǫtь ‘in my father's house there are many rooms’ (Mar. John 14:2)

existen?al impersonal: lacks referenJal subject i bystъ egda sěaše ‘and (it) happened as he was sowing’ (Mar. Mark 4:4)

existen?al possessive: with a daJve nominal ne bě ima čęda ‘they had no child’ (Mar. Luke 1:7)

posi?on/goal: indicaJng posiJon, source, or goal otcъ moi iže estъ na nebesьxъ ‘my father who is in heaven’ (Mar. Ma^. 16:17)

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The construc?onal profile of BYTI

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These nodes

emerge from the data

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Do these nodes

form a radial category?

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The gramma?cal profile of BYTI in the auxiliary construcJon

es-‐forms bū-‐forms shared forms

Gramma?cal profiles: arrangement of the nodes

•  Ten construcJons (≈ meanings ≈ nodes) have ten different grammaJcal profiles (= distribuJons of es-‐ and bū-‐forms of BYTI)

•  A correspondence analysis measures the distances between the construcJons in terms of the grammaJcal profiles

•  This gives us the arrangement of the nodes •  IF the arrangement yields a coherent radial category and

there is overlap in use of forms, BYTI is probably one verb (H1)

•  IF the arrangement does not yield a single radial category and there is specializa?on and contrast in use of forms, BYTI is probably two verbs (H2)

!

0 1 2 3 4

−0.5

0.0

0.5

1.0

1.5

Factor 1 (56.1 %)

Facto

r 2 (

21.3

%)

aux

auxiliaroid

copulacopular_benefactive

copular_impersonal

copular_possessive

existential

existential_impersonal

existential_possessiveposition_goal

1

2

34

5

Correspondence Analysis of the GrammaJcal Profiles of the Ten BYTI ConstrucJons: yields 5 nodes and radial category arrangement

(Auxiliary construcJon is actually much more peripheral due to subjuncJve,

which is removed in this plot)

Clustering of BYTI constructions and forms cluster construc?on es-‐ forms percent bū-‐ forms percent shared

forms percent

Cluster 1 auxiliary 203 95.8% 9 4.2% 0 0%

Cluster 2 existenJal impersonal

0 0% 47 100% 0 0%

Cluster 3 copula 746 81.0% 121 13.1% 54 5.9%

copular possessive

22 84.6% 4 15.4% 0 0%

copular benefacJve

28 59.6% 15 31.9% 4 8.5%

Cluster 4 existenJal 124 42.8% 147 50.7% 19 6.6%

existenJal possessive

22 42.3% 24 46.2% 6 11.5%

auxiliaroid 201 55.7% 134 37.1% 26 7.2%

posiJon/goal 326 76.3% 77 18.0% 24 5.6%

Cluster 5 copular impersonal

22

48.9% 23 51.1% 0 0%


forms percent



0 0% 47 100% 0 0%

Cluster 3 copula 746 81.0% 121 13.1% 54 5.9%

copular possessive

22 84.6% 4 15.4% 0 0%

copular benefacJve

28 59.6% 15 31.9% 4 8.5%



22 42.3% 24 46.2% 6 11.5%

auxiliaroid 201 55.7% 134 37.1% 26 7.2%

posiJon/goal 326 76.3% 77 18.0% 24 5.6%


22

48.9% 23 51.1% 0 0%

Two central clusters of construc?ons


forms percent



0 0% 47 100% 0 0%

Cluster 3 copula 746 81.0% 121 13.1% 54 5.9%

copular possessive

22 84.6% 4 15.4% 0 0%

copular benefacJve

28 59.6% 15 31.9% 4 8.5%



22 42.3% 24 46.2% 6 11.5%

auxiliaroid 201 55.7% 134 37.1% 26 7.2%

posiJon/goal 326 76.3% 77 18.0% 24 5.6%


22

48.9% 23 51.1% 0 0%

Three peripheral construc?ons


forms percent



0 0% 47 100% 0 0%

Cluster 3 copula 746 81.0% 121 13.1% 54 5.9%

copular possessive

22 84.6% 4 15.4% 0 0%

copular benefacJve

28 59.6% 15 31.9% 4 8.5%



22 42.3% 24 46.2% 6 11.5%

auxiliaroid 201 55.7% 134 37.1% 26 7.2%

posiJon/goal 326 76.3% 77 18.0% 24 5.6%


22

48.9% 23 51.1% 0 0%

Aside from two of the peripheral construc?ons, es-‐ and bū-‐forms overlap

and do not contrast


forms percent



0 0% 47 100% 0 0%

Cluster 3 copula 746 81.0% 121 13.1% 54 5.9%

copular possessive

22 84.6% 4 15.4% 0 0%

copular benefacJve

28 59.6% 15 31.9% 4 8.5%



22 42.3% 24 46.2% 6 11.5%

auxiliaroid 201 55.7% 134 37.1% 26 7.2%

posiJon/goal 326 76.3% 77 18.0% 24 5.6%


22

48.9% 23 51.1% 0 0%

Auxiliarioid is very different from

auxiliary


forms percent



0 0% 47 100% 0 0%

Cluster 3 copula 746 81.0% 121 13.1% 54 5.9%

copular possessive

22 84.6% 4 15.4% 0 0%

copular benefacJve

28 59.6% 15 31.9% 4 8.5%



22 42.3% 24 46.2% 6 11.5%

auxiliaroid 201 55.7% 134 37.1% 26 7.2%

posiJon/goal 326 76.3% 77 18.0% 24 5.6%


22

48.9% 23 51.1% 0 0%

Impersonals very different from personals

Outcome for BYTI

•  Our correspondence analysis shows exactly the structure of relationships we would expect to obtain for a polysemous verb like BYTI

•  In other words, we get a coherent radial category

•  Our findings support H1 that BYTI is a single, polysemous verb

PART THREE: Why Linguis?c Categories Should Be Cogni?vely Realis?c

•  A realisJc radial category network structure can be obtained objecJvely

•  However, a great deal of intuiJon/experJse is needed in order to – ensure that the input is properly annotated and – properly interpret the data

•  Only cogni?vely realis?c categories make it possible to join data analysis to linguis?c insights

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The$Radial$Categoryasan$ Emergent$Structure - UiT