Week 2. Optional infinitives and subject case GRS LX 865 Topics in Linguistics.

Week 2. Optional infinitives Week 2. Optional infinitives and subject caseand subject case

GRS LX 865GRS LX 865Topics in Topics in

LinguisticsLinguistics

Subject case errorsSubject case errors Various people have observed that kids Various people have observed that kids

learning English sometimes will use accusative learning English sometimes will use accusative subjects.subjects. Her play.Her play.

It turns out that there’s a sort of a correlation It turns out that there’s a sort of a correlation with the finiteness of the verb as well. with the finiteness of the verb as well. Finite Finite verbs go with nominative case, while nonfinite verbs go with nominative case, while nonfinite verbs seem to go with either nominative or verbs seem to go with either nominative or accusative case.accusative case.

But why But why cancan a nonfinite verb’s subject be nom? a nonfinite verb’s subject be nom?

Finiteness vs. case errorsFiniteness vs. case errors

Schütze & Wexler (1996)Nina1;11-2;6

Loeb & Leonard (1991)7 representative kids2;11-3;4

subject Finite Nonfinite Finite Nonfinite

he+she 255 139 436 75

him+her 14 120 4 28

% non-Nom 5% 46% 0.9% 27%

EPP and missing INFLEPP and missing INFL If there were just an IP, responsible for both If there were just an IP, responsible for both

NOM and tense, then they should go together NOM and tense, then they should go together (cf. “IP grammar” vs. “VP grammar”)(cf. “IP grammar” vs. “VP grammar”)

Yet, there are many cases of root infinitives with Yet, there are many cases of root infinitives with NOM subjectsNOM subjects

And, even ACC subjects seem to raise out of the And, even ACC subjects seem to raise out of the VP over negationVP over negation ( (me not gome not go).).

We can understand this once we consider IP to We can understand this once we consider IP to be split into TP and AgrP; tense and case are be split into TP and AgrP; tense and case are separated, but even one will still pull the subject separated, but even one will still pull the subject up out of VP. up out of VP. (ATOM:+Agr –Tns)(ATOM:+Agr –Tns)

What to make of the case What to make of the case errors?errors?

Case is assumed to be Case is assumed to be the jurisdiction of the jurisdiction of AgrSP and AgrOP.AgrSP and AgrOP.

So, nominative case So, nominative case can serve as an can serve as an unambiguous signal unambiguous signal that there is an that there is an AgrSP.AgrSP.

Accusative case, Accusative case, conversely, may conversely, may signal a missing signal a missing AgrSP.AgrSP.

Why are non-AgrSP Why are non-AgrSP subjects accusatives?subjects accusatives?

Probably a default Probably a default case in English:case in English: Who’s driving? Me. Me Who’s driving? Me. Me

too. It’s me.too. It’s me. Other languages seem Other languages seem

not to show this not to show this “accusative subject” “accusative subject” error but also seem to error but also seem to have a nominative have a nominative default (making an default (making an error undetectable).error undetectable).

““ATOM”ATOM” Schütze & Wexler Schütze & Wexler

propose a propose a mmodel of odel of this in which the this in which the case errors are a case errors are a result of being able result of being able to either to either oomit mit AAgrSP or grSP or TTense.ense.

For a subject to be For a subject to be in nominative case, in nominative case, AgrSP must be AgrSP must be therethere (TP’s (TP’s presence is presence is irrelevant).irrelevant).

For a finite verb, For a finite verb, both both TP and TP and AgrSP must be there.AgrSP must be there. English English inflection (3sg present –inflection (3sg present –ss) ) relies on both. relies on both. If one or the If one or the other is missing, we’ll see an other is missing, we’ll see an infinitiveinfinitive (i.e. bare stem). (i.e. bare stem).

Thus, predicted:Thus, predicted: finite finite (AgrSP+TP) verbs show Nom (AgrSP+TP) verbs show Nom (AgrSP), but only half of the (AgrSP), but only half of the nonfinite verbs (not both nonfinite verbs (not both AgrSP and TP) show Nom AgrSP and TP) show Nom (AgrSP). We should (AgrSP). We should notnot see see finite+Acc.finite+Acc.

Agr/T Omission Model Agr/T Omission Model (ATOM)(ATOM)

Adult clause structure:Adult clause structure:

AgrPAgrP

NOMNOMii AgrAgr

AgrAgr TPTP

ttii T T

TT VPVP

ATOMATOM

Kiddie clause, missing TP (—TNS):Kiddie clause, missing TP (—TNS):

AgrPAgrP

NOMNOMii AgrAgr

AgrAgr

VPVP

ATOMATOM

Kiddie clause, missing AgrP (—AGR):Kiddie clause, missing AgrP (—AGR):

TPTP

ACC ACC defaultdefaultii T T

TT VPVP

Pronunciation of EnglishPronunciation of English T+AgrS(+V) is T+AgrS(+V) is

pronounced like:pronounced like:

/s//s/ if we have if we have features [3, sg, features [3, sg, present]present]

/ed//ed/ if we have the if we have the feature [past]feature [past]

ØØ otherwise otherwise

Layers of “default”, Layers of “default”, most specific first, most specific first, followed by next most followed by next most specific specific (“Distributed (“Distributed Morphology”, Halle & Morphology”, Halle & Marantz 1993)Marantz 1993)..

Notice: Notice: 3sg present 3sg present –s–s requires both TP and requires both TP and AgrSP, but past AgrSP, but past –ed–ed requires only TP (AgrSP requires only TP (AgrSP might be missing, so we might be missing, so we might expect some might expect some accusative subjects of accusative subjects of past tense verbs).past tense verbs).

One prediction of ATOMOne prediction of ATOM +AGR+TNS: NOM with inflected verb (+AGR+TNS: NOM with inflected verb (--

ss)) +AGR–TNS: NOM with bare verb+AGR–TNS: NOM with bare verb ––AGR+TNS: AGR+TNS: defaultdefault (ACC) with bare (ACC) with bare

verbverb ––AGR–TNS: GEN with bare verbAGR–TNS: GEN with bare verb

(the GEN case was not discussed by Wexler (the GEN case was not discussed by Wexler 1998, but see Schütze & Wexler 1996)1998, but see Schütze & Wexler 1996)

Nothing Nothing predicts Acc with inflected verb.predicts Acc with inflected verb.

Finite pretty much always Finite pretty much always goes with a nominative goes with a nominative

subject.subject.Schütze & Wexler (1996)Nina1;11-2;6

Loeb & Leonard (1991)7 representative kids2;11-3;4

subject Finite Nonfinite Finite Nonfinite

he+she 255 139 436 75

him+her 14 20 4 28

% non-Nom 5% 46% 0.9% 27%

ATOM and morphologyATOM and morphology [+3sg +pres] = -s[+3sg +pres] = -s [+past] = -ed[+past] = -ed — — = Ø= Ø

[+masc +3sg +nom][+masc +3sg +nom]play+[3sg+pres]play+[3sg+pres] he plays.he plays.

[+2sg +nom][+2sg +nom]play+[2sg +past]play+[2sg +past] you play.you play.

But is this knowledge But is this knowledge built-in? built-in? HintHint: no.: no.

[+masc, +3sg, +nom] = [+masc, +3sg, +nom] = hehe

[+masc, +3sg, +gen] = his[+masc, +3sg, +gen] = his [+masc, +3sg] = him[+masc, +3sg] = him [+fem, +3sg, +nom] = she[+fem, +3sg, +nom] = she [+fem, +3sg] = her[+fem, +3sg] = her [+1sg, +nom] = I[+1sg, +nom] = I [+1sg, +gen] = my[+1sg, +gen] = my [+1sg] = me[+1sg] = me [+2, +gen] = your[+2, +gen] = your [+2] = you[+2] = you

ATOM and morphologyATOM and morphology What if the child What if the child

produces a lot of produces a lot of utterances likeutterances like her sleepingher sleeping her playher play

and evenand even her sleepsher sleeps her goes to schoolher goes to school

but never uses the but never uses the word word sheshe??

ATOM predicts that ATOM predicts that agreement and agreement and nominative case nominative case should correlate.should correlate.

Her goes to schoolHer goes to school is predicted never is predicted never to occur.to occur.

So does this child’s So does this child’s use of use of her goes to her goes to schoolschool mean ATOM mean ATOM is wrong?is wrong?

Schütze (2001, Schütze (2001, inter aliainter alia)) No.No. Her goes to schoolHer goes to school is is

not not necessarily necessarily a a counterexample to counterexample to ATOM (although it is a ATOM (although it is a candidate).candidate).

Morphology must be Morphology must be learned and is learned and is crosslinguistically crosslinguistically variable.variable.

SheShe is known to is known to emerge rather late emerge rather late compared to other compared to other pronouns.pronouns.

If the kid thinks If the kid thinks herher isis the the nominative feminine 3sg nominative feminine 3sg pronoun, pronoun, her goes to her goes to schoolschool is perfectly is perfectly consistent with ATOM.consistent with ATOM.

Hence, we should really Hence, we should really only count only count herher+agr +agr correlations from kids who correlations from kids who have demonstrated that have demonstrated that they know they know sheshe..

ATOM and morphologyATOM and morphology Morphology (under Morphology (under

“Distributed Morphology”) “Distributed Morphology”) is a system of defaults.is a system of defaults.

The most specified form The most specified form possible is used.possible is used.

Adult English specifies Adult English specifies herher as a feminine 3sg pronoun, as a feminine 3sg pronoun, and and sheshe as a as a nominative nominative feminine 3sg pronoun.feminine 3sg pronoun.

If the kid doesn’t know If the kid doesn’t know sheshe, , the result will be that all the result will be that all feminine 3sg pronouns will feminine 3sg pronouns will come out as come out as herher. That’s just . That’s just how you pronounce how you pronounce nominative 3sg feminine, if nominative 3sg feminine, if you’re the kid.you’re the kid. Just like adult Just like adult youyou..

[+masc, +3sg, +nom] = [+masc, +3sg, +nom] = hehe

[+masc, +3sg, +gen] = his[+masc, +3sg, +gen] = his [+masc, +3sg] = him[+masc, +3sg] = him [+fem, +3sg, +nom] = she[+fem, +3sg, +nom] = she [+fem, +3sg] = her[+fem, +3sg] = her [+1sg, +nom] = I[+1sg, +nom] = I [+1sg, +gen] = my[+1sg, +gen] = my [+1sg] = me[+1sg] = me [+2, +gen] = your[+2, +gen] = your [+2] = you[+2] = you

Rispoli (2002, Rispoli (2002, inter aliainter alia)) Rispoli has his own Rispoli has his own

theory of theory of herher--errors.errors. Pronoun morphology is Pronoun morphology is

organized into “tables” organized into “tables” (paradigms) basically, (paradigms) basically, where each form has a where each form has a certain weight.certain weight.

When a kid is trying to When a kid is trying to pronounce a pronoun, pronounce a pronoun, s/he attempts to find s/he attempts to find the entry in the table the entry in the table and pronounce it.and pronounce it.

The kid’s success in The kid’s success in finding the form is finding the form is affected by “gravity”. affected by “gravity”. “Heavier” forms are “Heavier” forms are more likely to be picked more likely to be picked when accessing the when accessing the table, even if it’s not table, even if it’s not quite the right form. If quite the right form. If it’s close and it’s heavy, it’s close and it’s heavy, it’ll win out a lot of the it’ll win out a lot of the time.time.

HerHer by virtue of being by virtue of being both acc and gen is both acc and gen is extra-heavy, and pulls extra-heavy, and pulls the kid in fairly often.the kid in fairly often.

Her playsHer plays ATOM and Rispoli ATOM and Rispoli

make different make different predictions with predictions with respect to respect to her playsher plays..

ATOM says it should ATOM says it should never happen (up to never happen (up to simple performance simple performance error)error)

Rispoli says case Rispoli says case errors are independent errors are independent of agreement, of agreement, her her playsplays is perfectly is perfectly possible, even possible, even expected.expected.

Rispoli’s complaints Rispoli’s complaints about Schütze’s studies:about Schütze’s studies:

Excluding kids who Excluding kids who happen not to produce happen not to produce sheshe in the transcript in the transcript under evaluation is not under evaluation is not good enough. The good enough. The assumption is that this assumption is that this learning is learning is monotonicmonotonic, , so if the kid so if the kid everever used used sheshe (productively) in the (productively) in the past, the past, the herher errors errors should not be excluded.should not be excluded.

MonotonicityMonotonicity Schütze assumes that Schütze assumes that

use of use of sheshe is a matter of is a matter of knowledgeknowledge of of sheshe. Once . Once the kid knows it, and the kid knows it, and given that the adult given that the adult version of the kid will version of the kid will know it, it’s there, for know it, it’s there, for good.good.

Rispoli claims that the Rispoli claims that the “weight” of “weight” of sheshe can can fluctuate, so that it fluctuate, so that it could be “known” but could be “known” but mis-retrieved later if mis-retrieved later if herher becomes too heavy. becomes too heavy.

Rispoli (2002) set Rispoli (2002) set out to show that out to show that there is a certain there is a certain amount of “yo-amount of “yo-yo’ing” in the yo’ing” in the production of production of sheshe..

We’ll focus on Nina, We’ll focus on Nina, for whom we can get for whom we can get the data.the data.

Nina Nina sheshe vs. vs. herher

Rispoli’s counts Rispoli’s counts show Nina using show Nina using sheshe from basically from basically the outset of her the outset of her use of pronouns, use of pronouns, and also shows a and also shows a decrease of use of decrease of use of sheshe at 2;5. at 2;5.

sheshe herher

2;22;213-1513-15

224%4%

434396%96%

2;32;316-1916-19

118%8%

121292%92%

2;42;420-2320-23

1114%14%

6686%86%

2;52;524-3124-31

779%9%

737391%91%

Checking Rispoli’s Checking Rispoli’s countscounts

2;22;2 *CHI: she have hug a lady .*CHI: she have hug a lady .

*CHI: she have jamas@f on .*CHI: she have jamas@f on . 2;32;3

*MOT: does she like it ?*MOT: does she like it ? *CHI: she drink apple juice .*CHI: she drink apple juice . *CHI: her like apple juice .*CHI: her like apple juice .

2;42;4 *MOT: he's up there ?*MOT: he's up there ? *CHI: no # she's not up *CHI: no # she's not up

there .there . *CHI: he's up there .*CHI: he's up there .

These are the These are the times when Nina times when Nina used used sheshe (twice (twice at 2;2, once at at 2;2, once at 2;3, once at 2;4).2;3, once at 2;4).

Rispoli found 7 Rispoli found 7 at 2;5, we’ll deal at 2;5, we’ll deal with them later.with them later.

CheckingChecking 2;22;2

*CHI: helping her have a *CHI: helping her have a yellow blanket .yellow blanket .

*MOT: she has a yellow *MOT: she has a yellow blanket ?blanket ?

*CHI: yeah [= yes] .*CHI: yeah [= yes] . *CHI: her's ok .*CHI: her's ok . *CHI: her ok .*CHI: her ok . *MOT: she's ok ?*MOT: she's ok ? *CHI: ok .*CHI: ok . *CHI: her's ok .*CHI: her's ok . *CHI: her ok .*CHI: her ok . *CHI: her's ok .*CHI: her's ok . *MOT: she's ok .*MOT: she's ok .

These three and one other These three and one other time Nina said time Nina said her’s okher’s ok are are the only candidate the only candidate counterexamples at 2;2.counterexamples at 2;2.

At 2;2, 45 At 2;2, 45 herher+bare verb.+bare verb. (R got 43, possibly (R got 43, possibly

including including her’s okher’s ok)) At 2;3, no candidate At 2;3, no candidate

counterexamples, 14 counterexamples, 14 herher+bare verbs.+bare verbs. (R got 12)(R got 12)

At 2;4 none, 7 At 2;4 none, 7 herher+bare.+bare. (R got 6)(R got 6)

CheckingChecking *MOT: what happened when I *MOT: what happened when I

shampooed Miriam yesterday ?shampooed Miriam yesterday ? *CHI: her was cried .*CHI: her was cried .

*MOT: oh # there's the dolly's *MOT: oh # there's the dolly's bottle .bottle .

*CHI: her's not going to drink it .*CHI: her's not going to drink it .

*MOT: I'll start washing it .*MOT: I'll start washing it . *MOT: see how clean it comes ?*MOT: see how clean it comes ? *MOT: you want to use the pot ?*MOT: you want to use the pot ? *CHI: a little bit .*CHI: a little bit . *CHI: her don't .*CHI: her don't . *CHI: her's not dirty .*CHI: her's not dirty . *CHI: not dirty .*CHI: not dirty .

2;5:2;5: I found about I found about

76 76 herher+bare/past +bare/past verbs.verbs.

I found 3 I found 3 potential potential counterexamplcounterexamples.es.

Bottom line?Bottom line? It doesn’t seem like It doesn’t seem like

anything was anything was particularly particularly affected, even if affected, even if Nina’s early files Nina’s early files were fully included.were fully included.

The number of The number of possible possible counterexamples counterexamples seems within the seems within the “performance “performance error” range.error” range.

The point about variation The point about variation in usage of in usage of sheshe is valid, is valid, worth being aware of the worth being aware of the assumptions and being assumptions and being sure we’re testing the sure we’re testing the right things.right things.

Rispoli was trying to make Rispoli was trying to make the point that if we’d the point that if we’d accidentally missed a accidentally missed a sheshe in the early files, we might in the early files, we might have excluded have excluded counterexamples there.counterexamples there.

Yet, even including Yet, even including everythingeverything, the , the asymmetry is strong.asymmetry is strong.

Implementing ATOMImplementing ATOM

The basic idea: The basic idea: In adult clauses, the In adult clauses, the subject needs to move subject needs to move bothboth to SpecTP to SpecTP and (then)and (then) to SpecAgrP. to SpecAgrP.

This needs to happen because T This needs to happen because T “needs” something in its specifier “needs” something in its specifier (≈EPP) and so does Agr.(≈EPP) and so does Agr.

The subject DP can “solve the The subject DP can “solve the problem” for both T and for Agr—problem” for both T and for Agr—for for an adultan adult..


Implementation:Implementation: For adults: For adults: T needs a D feature.T needs a D feature. Agr needs a D feature.Agr needs a D feature. The subject, happily, The subject, happily, hashas a D feature. a D feature. The subject moves to SpecTP, takes care of The subject moves to SpecTP, takes care of

T’s need for a D feature (the subject T’s need for a D feature (the subject “checks” the D feature on T). The T feature “checks” the D feature on T). The T feature loses its need for a D feature, but the loses its need for a D feature, but the subject still has its D feature (the subject is subject still has its D feature (the subject is still a DP).still a DP).

The subject moves on, to take care of Agr.The subject moves on, to take care of Agr.


Implementation:Implementation: For kids: For kids: Everything is the same except that Everything is the same except that the the

subject can only solve subject can only solve one one problem problem before quittingbefore quitting. It “loses” its D feature . It “loses” its D feature after helping out either T or Agr.after helping out either T or Agr.

Kids are constrained by the Kids are constrained by the Unique Unique Checking Constraint Checking Constraint that says subjects that says subjects (or their D features) can only “check” (or their D features) can only “check” another feature once.another feature once.

So the kids are in a bind.So the kids are in a bind.

Implementing ATOMImplementing ATOM Kids in a pickle:Kids in a pickle: The only options open to the The only options open to the

kids are:kids are: Leave out TP Leave out TP (keep AgrP, the subject can solve (keep AgrP, the subject can solve

Agr’s problem alone). Agr’s problem alone). Result: nonfinite verb, nom Result: nonfinite verb, nom case.case.

Leave out AgrP Leave out AgrP (keep TP, the subject can solve T’s (keep TP, the subject can solve T’s problem alone). problem alone). Result: nonfinite verb, default case.Result: nonfinite verb, default case.

Violate the UCC Violate the UCC (let the subject do both things (let the subject do both things anyway). anyway). Result: finite verb, nom case.Result: finite verb, nom case.

No matter which way you slice it, the kids No matter which way you slice it, the kids have to do something “wrong”. At that point, have to do something “wrong”. At that point, they choose randomly (but cf. Legendre et al.)they choose randomly (but cf. Legendre et al.)

Minimalist terminologyMinimalist terminology Features come in two relevant kinds: Features come in two relevant kinds:

interpretable interpretable and and uninterpretableuninterpretable.. Either kind of feature can be involved in a Either kind of feature can be involved in a

“checking”—only interpretable features survive.“checking”—only interpretable features survive. The game is to have no uninterpretable features The game is to have no uninterpretable features

left at the end.left at the end. ““T needs a DT needs a D” means “” means “T has an uninterpretable T has an uninterpretable

[D] feature[D] feature” and the subject (with its normally ” and the subject (with its normally interpretable [D] feature) comes along and the interpretable [D] feature) comes along and the two features “check”, the interpretable one two features “check”, the interpretable one survives. survives. UCC=D uninterpretable on subjects?UCC=D uninterpretable on subjects?

NS/OI via UCCNS/OI via UCC

An old idea about NS languages is that they An old idea about NS languages is that they arise in languages where Infl is “rich” enough arise in languages where Infl is “rich” enough to to identifyidentify the subject. the subject.

Maybe in NS languages, AgrS does not Maybe in NS languages, AgrS does not needneed a a DD (it may in some sense be nouny enough to (it may in some sense be nouny enough to say that it say that it isis, or already , or already hashas, D)., D).

If AgrS does not need a D, the subject is free If AgrS does not need a D, the subject is free to check off T’s D-feature and be done.to check off T’s D-feature and be done.

The spreadsheetThe spreadsheet A spreadsheet is A spreadsheet is

fundamentally a big fundamentally a big table, with rows and table, with rows and columns, and each columns, and each cellcell can contain data can contain data of any sort.of any sort.

What’s fancy about What’s fancy about spreadsheet programs spreadsheet programs is they allow you to is they allow you to enter enter formulaeformulae into a into a cell, computing the cell, computing the value based on the value based on the values in other cells.values in other cells.

AA BB

11 widthwidth 44

22 heighheightt

22

33 areaarea 88

44

=B1*B2

The spreadsheetThe spreadsheet The most obvious The most obvious

applications of this are applications of this are mathy: financial, mathy: financial, statistical, etc.statistical, etc.

But this can be quite But this can be quite helpful in organizing our helpful in organizing our data as we search through data as we search through CHILDES.CHILDES.

This is much better than This is much better than simply marking things simply marking things down on paper, since it down on paper, since it counts everything for you counts everything for you and makes changes easy.and makes changes easy.

AA BB CC

11 fifinn

nononfinfinn

utteranceutterance

22 00 11 he gohe go

33 11 00 she wentshe went

44 11 11

=SUM(B2:B3)

What CLAN (combo) What CLAN (combo) gives usgives us

We get a text We get a text file with some file with some information information about the about the search at the search at the top, and then top, and then groups of groups of utterances and utterances and context, with context, with the found child the found child utterance in utterance in the middle.the middle.

combo +t*CHI +w2 -w2 [email protected] peter07a.chacombo +t*CHI +w2 -w2 [email protected] peter07a.chaSun Sep 8 00:08:11 2002Sun Sep 8 00:08:11 2002combo (02-Aug-2002) is conducting analyses on:combo (02-Aug-2002) is conducting analyses on: ONLY speaker main tiers matching: *CHI;ONLY speaker main tiers matching: *CHI;********************************************************************************From file <peter07a.cha>From file <peter07a.cha>--------------------------------------------------------------------------------*** File "peter07a.cha": line 52.*** File "peter07a.cha": line 52.*MOT:*MOT: the wire .the wire .*PAT:*PAT: oh <the &te> [//] the wire's gone ?oh <the &te> [//] the wire's gone ?*CHI:*CHI: xxx # need it # (1)my need it # xxx .xxx # need it # (1)my need it # xxx .*CHI:*CHI: xxx .xxx .*PAT:*PAT: uhhuh .uhhuh .--------------------------------------------------------------------------------*** File "peter07a.cha": line 207.*** File "peter07a.cha": line 207.*CHI:*CHI: xxx # xxx .xxx # xxx .*PAT:*PAT: what ?what ?*CHI:*CHI: this is # (1)I'll show you # (2)I'll show you .this is # (1)I'll show you # (2)I'll show you .*LOI:*LOI: you'll show me ?you'll show me ?*LOI:*LOI: ok .ok .--------------------------------------------------------------------------------*** File "peter07a.cha": line 329.*** File "peter07a.cha": line 329.

The planThe plan Not every child Not every child

utterance is utterance is relevant.relevant.

The first part of The first part of our plan is to our plan is to isolate the child isolate the child utterances from utterances from the context so the context so we can narrow we can narrow down on just the down on just the relevant ones.relevant ones.


The planThe plan We’ll start by We’ll start by

making a making a formula that formula that counts the counts the number of lines number of lines that start with that start with “*” since the “*” since the last line of last line of dashes.dashes.

The child’s The child’s utterance will utterance will be the fourth be the fourth one.one.


Computing “stars”Computing “stars” We’ll do this with a fancy We’ll do this with a fancy

formula.formula. LEFT(LEFT(C4C4,,33)) gives us the gives us the

first (leftmost) first (leftmost) 33 characters of the characters of the transcript line in transcript line in C4C4..

(LEFT(C4,3)=“---”)(LEFT(C4,3)=“---”) will be will be 1 if those three characters 1 if those three characters are “---” and 0 otherwise.are “---” and 0 otherwise.

Subtracting that from 1 Subtracting that from 1 will be 0 for “---” lines, and will be 0 for “---” lines, and 1 otherwise.1 otherwise.

AA BB CC

11 00 --------------------------------

22 11 *** File "peter07*** File "peter07

33 22*MOT:*MOT: the wirethe wire

44 33*PAT:*PAT: oh <theoh <the

=((LEFT(C4,1)="*")+A3)*(1-(LEFT(C4,3)="---"))

Computing “stars”Computing “stars” LEFT(C4,1)=“*”LEFT(C4,1)=“*” will will

be 1 if the transcript be 1 if the transcript line starts with “*”.line starts with “*”.

We add that (1 if We add that (1 if there’s a “*”) to the there’s a “*”) to the previous number (in previous number (in A3, for cell A4). That A3, for cell A4). That is, count the “stars”.is, count the “stars”.

Finally, for “---” Finally, for “---” multiply by zero multiply by zero (restart the count).(restart the count).

AA BB CC

11 00 --------------------------------

22 11 *** File "peter07*** File "peter07

33 22*MOT:*MOT: the wirethe wire

44 33*PAT:*PAT: oh <theoh <the

=((LEFT(C4,1)="*")+A3)*(1-(LEFT(C4,3)="---"))

Counting child Counting child utterancesutterances

Column B will keep Column B will keep track of how many track of how many child utterances child utterances there have been.there have been.

That is, how many That is, how many times A registers 4.times A registers 4.

The formula copies The formula copies the previous the previous number and adds number and adds one if column A one if column A has 4 in it.has 4 in it.

AA BB CC

33 22 00 *MOT:*MOT: the wirethe wire

44 33 00 *PAT:*PAT: oh <theoh <the

55 44 11*CHI:*CHI: xxx # need xxx # need it # (1)my need itit # (1)my need it

66 55 11*CHI:*CHI: xxxxxx

=B5+(A6=4)

Getting the kid utt’s Getting the kid utt’s alonealone

Then, we’ll start a fresh Then, we’ll start a fresh sheet and copy in just the sheet and copy in just the child utterances.child utterances.

The idea:The idea: in row 1, we’ll in row 1, we’ll want to find the utterance want to find the utterance where column B in our where column B in our previous spreadsheet is previous spreadsheet is (first) 1, in row 2…(first) 1, in row 2…

The utterance is in column The utterance is in column C (column 3). We can also C (column 3). We can also refer to this as refer to this as RRrowrowCCcolumn.column.

AA BB CC

33 22 00 *MOT:*MOT: the wirethe wire

44 33 00 *PAT:*PAT: oh <theoh <the

55 44 11*CHI:*CHI: xxx # need xxx # need it # (1)my need itit # (1)my need it

66 55 11*CHI:*CHI: xxxxxx

C6 or R6C4


Our earlier Our earlier spreadsheet is spreadsheet is named “raw”, so named “raw”, so raw!A1raw!A1 is the is the content of A1 on content of A1 on sheet “raw”, sheet “raw”, raw!raw!B1:B800B1:B800 refers to refers to the cells in column 2, the cells in column 2, rows 1 through 800.rows 1 through 800.

ROW(A4)ROW(A4) is simply is simply the row number of the row number of cell A4 (namely, 4).cell A4 (namely, 4).

AA BB

11 55 *CHI:*CHI: my need my need

22 1122

*CHI:*CHI: I’ll showI’ll show

33 1199

*CHI:*CHI: xxxxxx

44 2266

*CHI:*CHI: xxxxxx

=MATCH(ROW(A4), raw!B1:B800, 0)


MATCH(a, cells, sort)MATCH(a, cells, sort) finds the first “a” in finds the first “a” in cells when cells when sort sort is 0.is 0.

In this case, we’re In this case, we’re looking for the first 4 looking for the first 4 between B1 and between B1 and B800 on the “raw” B800 on the “raw” spreadsheet.spreadsheet.

The resulting number The resulting number is the row number is the row number (from “raw”).(from “raw”).

AA BB


22 1122


33 1199

*CHI:*CHI: xxxxxx

44 2266

*CHI:*CHI: xxxxxx

=MATCH(ROW(A4), raw!B1:B800, 0)


=INDIRECT(“raw!=INDIRECT(“raw!R2C2”, FALSE)R2C2”, FALSE) will will copy the contents of copy the contents of raw!B2 raw!B2 (FALSE means (FALSE means to use the R2C2 type to use the R2C2 type reference, not the B2 reference, not the B2 type).type).

What we’re doing is What we’re doing is using the row number using the row number we just found (in we just found (in column A), and column column A), and column 3 (where the 3 (where the utterances are).utterances are).

raw!R26C3raw!R26C3

AA BB


22 1122


33 1199

*CHI:*CHI: xxxxxx

44 2266

*CHI:*CHI: xxxxxx

=INDIRECT("raw!R” & A2 & "C3", FALSE)

The plan continuesThe plan continues

At this point, we’ll At this point, we’ll have the child have the child utterances alone, utterances alone, so we can look at so we can look at them and see if them and see if they contain a they contain a subject pronoun subject pronoun (and see which one) (and see which one) or if they contain or if they contain an irrelevant an irrelevant match.match.

My need it.My need it. My pencil.My pencil. I’ll show you.I’ll show you. Show me.Show me. … …


We’ll do a coloring We’ll do a coloring trick to “grey out” trick to “grey out” the things we the things we marked as marked as irrelevant.irrelevant.

We’ll code the We’ll code the utterances for finite utterances for finite verbs, nonfinite verbs, nonfinite verbs, or ambiguous verbs, or ambiguous forms.forms.

my goingmy going you goyou go I’ll show youI’ll show you he gohe go he runshe runs ……


After that, we’ll After that, we’ll bring back the bring back the context with a context with a similar method so similar method so we can make sure we can make sure that we’re not that we’re not counting counting repetitions, etc.repetitions, etc.

And finally, we’ll And finally, we’ll count up how count up how many nominative many nominative subjects come with subjects come with finite verbs, how finite verbs, how many accusative many accusative subjects come with subjects come with nonfinite verbs, nonfinite verbs, etc.etc.

What to do nextWhat to do next

We’ll try this out We’ll try this out on the peter07 file.on the peter07 file.

Later, you’ll adapt Later, you’ll adapt this to look at the this to look at the nina13.cha (with nina13.cha (with not a great deal of not a great deal of modification).modification).

Run through the Run through the steps on the web steps on the web page (or printout), page (or printout), now that we know now that we know what it’s doing.what it’s doing.

Comments about nina13Comments about nina13 When I did it…When I did it… I found about 70 relevant utterances (where I found about 70 relevant utterances (where

there is a pronoun subject and the verb is there is a pronoun subject and the verb is unambiguous) to pass on to the “subjects” sheet.unambiguous) to pass on to the “subjects” sheet.

Of those I omitted around 10 as repetitions or Of those I omitted around 10 as repetitions or otherwise uninformative.otherwise uninformative.

Be particularly careful about the lower bounds Be particularly careful about the lower bounds on these larger blocks—nina13 is a bigger file on these larger blocks—nina13 is a bigger file than peter07, and so you will occasionally need than peter07, and so you will occasionally need to increase some of the numbers to get all of the to increase some of the numbers to get all of the utterances in.utterances in.

Week 2. Optional infinitives and subject case GRS LX 865 Topics in Linguistics.

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