Corpus-based computational linguistics: A practical investigation of the procedures involved in the selection, study and exploitation of a relevant corpus


This paper charts a corpus analysis research investigation which was conducted in response to a classroom question. The linguistic features under investigation are “used to” and “be used to”; two grammatical forms whose constructional similarity often causes problems for beginner-level students.

This intentionally limited study outlines, by way of a step-by-step approach, the practical procedures involved in the assimilation and manipulation of computer-generated data. It is hoped that novice investigators may gain some valuable insight as to what even simplistic inquiries can bring for themselves as linguistic theorists, and to their learners embarking on a greater understanding of language meaning and usage.

A Brief History of Corpus Linguistics

Studies of language can be divided into two main areas: studies of structure and studies of use. Corpus analysis (CA) focuses on the second of these, studying actual language used in naturally occurring texts. Ever since Firth (1957) stated that “You shall know a word by the company it keeps”, it has been a practice in linguistics to classify words not only on the basis of their meanings, but also on the basis of their co-occurrence with other words. However, in a purely practical sense it is only in recent times that machines have given us the ability to identify these relationships in a meaningful and significant way.

From the simple listing of words in the Middle Ages by hand, to the earliest corpus-based analyses of literary styles, through to the first modern electronically readable corpus, the Brown University Corpus of American English, (and its close cousins the Lancaster-Oslo/Bergen corpus and the Kolhapur Corpus), the computer-aided analysis of vast amounts of authentic data has come a long way in a very short time. Almost half a century ago Firth (1957: 31) made the following prophetic statement: “The use of machines in linguistic analysis is now established”. John Sinclair (1991: 1) describes the evolution through the last three decades in the following way: “ Thirty years ago when this research started it was considered impossible to process texts of several million words in length. Twenty years ago it was considered marginally possible but lunatic. Ten years ago it was considered quite possible but still lunatic. Today it is very popular”. This popularity has led to an increased understanding of the relationship of meaning to form as formal patterns, previously undetected, have come to light. Sinclair states again, “At the very least, the quality of linguistic evidence is going to be improved out of all recognitionq¥Êt is my belief that a new understanding of the nature and structure of language will shortly be available as a result of the examination by computer of large collections of texts” (1991b: 489). Stubbs (1996) concurs, “computer-assisted analysis of texts and corpora can provide new understanding of form-meaning relations”.

It should be noted that CA involves far more than using computers for the simple counting and quantifying of linguistic features into sets of statistics. Though this may be seen as the first step in a two-stage process, it is the subsequent, qualitative analysis that provides the more revealing evidence “to propose functional interpretations explaining why the patterns exist” (Biber, Conrad & Reppen, 1998: 9). As a practical investigation, however, this paper focuses primarily on the procedures involved in obtaining and manipulating the data required to create a corpus, and while it does present some insight into possible pedagogic considerations and offer tentative conclusions based on corpus generated evidence, its scope is intentionally, limited.

Choosing a Corpus

Source, size and selection

In response to a recent classroom inquiry, the linguistic features under investigation are “used to” and “be used to”; two grammatical forms whose constructional similarity often causes problems for beginner-level students. For the purposes of this investigation I chose to use two established corpora, the Lancaster-Oslo/Bergen Corpus (LOB), of British English established by Geoffrey Leech and Jan Svartvik, and its American counterpart, the Brown University Corpus of American English (Brown), running parallel investigations under different methodological conditions. The two corpora are very similar in design: each taken from a total of some five hundred texts across a wide-range of registers, a combined total of approximately two million words.

Size is a prime concern for successful corpus-based lexicographic research. As Biber et al. warn: “To study the meaning and use of words, we need a very large corpus — a 1-million word corpus will not provide sufficient data for many words to allow for meaningful generalizations” (1998: 30). However, with more common words in a text of this size, frequencies are generally considered to be quite reliable. At a million or so words each, I was hoping that my choice of general purpose corpora would provide enough evidence to sufficiently highlight linguistic elements for possible future pedagogic exploitation.


As primarily a practical research study, I chose to conduct this investigation employing a number of differing methods. In the first instance, I examined the LOB corpus using a CD-ROM provided by the International Computer Archive of Modern English (ICAME), running the analysis through a software application, the Aston Text Analyser (ATA), supplied by Aston University. I also used part of the LOB corpus to examine the practical problems one might encounter in the creation of a pedagogic corpus, established corpora not always being readily available for investigation and exploitation.

As a reflection of recent advances in Internet technology, I was also interested in conducting a limited parallel study, making use of an on-line version of the Brown corpus, a free but time-restricted service provided by the University of Pennsylvania's Linguistic Data Consortium, (LDC). Details of distribution and copyright restrictions pertaining to both texts are included, (Appendix C).

It should be noted here that although the Brown corpus is also supplied on the ICAME CD-ROM, I chose not to access it in the traditional way preferring instead to examine the benefits and shortcomings of locating and accessing corpora via the alternative, and increasingly popular, on-line method.

Equipment Used

The study was conducted with the aid of a generic desktop personal computer running the Windows operating system. Software support was provided by the WinATA Mark 2 text analyser, a word processor, MS-Word 97 and an Optical Character Recognition (OCR) program, Caere Omni-Page Pro 9.0 used in conjunction with a flatbed scanner.

Data Input: Scanning and OCR

Equipment and procedure

In some instances, teachers and researchers may not have access to established corpora due to resource limitations. In other cases, most notably for investigations in English for Specific Purposes (ESP), it might be necessary to manually create a specific pedagogic corpus. In creating such a corpus for use in CA, one possible means of inputting data is to scan text directly into a computer using a suitable combination of hardware and software. In order to explore the limitations of such a procedure, I used a Microtek ScanMaker X6 scanner, a low budget flatbed model, together with Caere Omni-Page Pro 9.0 OCR software, which was supplied as part of the scanner package.

For the limited purposes of this exercise, I first selected a section of some five hundred words from my LOB corpus, cut and pasted them into a new document and saved this as a separate text file. This was then printed onto a standard sheet of A4 paper, and then scanned directly into the computer. An almost flawless text conversion is testimony to the development of OCR software in recent times. A few years ago a similar exercise may well have resulted in a bout of severe frustration, even when scanning a simple page of text. These days, more advanced programs such as Omni-Page Pro offer much greater speed, reliability and flexibility, especially when integrated into established word processing applications such as Word and Word Perfect. Carefully scanned pages of text assimilated in this way can form the basis for a ‘personal’ pedagogic corpus, to be subsequently examined by a suitable text analysis program.

Some Points to Note

There are two significant considerations that can effect the quality of the final output from the scanning procedure. Firstly, and most importantly, is the quality and condition of the document that one wishes to scan. I was using a clearly printed black text on a clean sheet of white plain paper. Highly colored, glossy, marked or even creased papers have all been known to cause problems with OCR software. The second consideration relates to the complexity of the document. As my inquiry revealed, regular text is not really a problem for this kind of application. However, when one mixes text, graphics and tables, more time needs to be spent in the setup process before attempting the conversion. I also found in this exercise that the software occasionally flagged correct words simply because they were not in the dictionary it was using.



Installation of the ATA software suite is via CD-ROM. It is important to note during the installation process that in order for the software to function correctly, all files must be extracted into the same location and not into separate folders. Correct installation creates two executable programs; ataIndex and ataInsight which must be run separately, one after the other. The first of these, as the name suggests, creates and indexes the corpus. In the case of LOB, this entails specifying the correct path for the location of the text to be indexed and titling the project appropriately. When the indexing has been completed, it is then necessary to run the second application, ataInsight. This opens an ‘Open ATA project’ window in which the now indexed LOB text can be found. On selecting ‘OK’, the program starts its analysis of the chosen project.

Frequency and filter

My investigation is to specifically look for occurrences of “used to” within the corpus. To do this, it is first necessary to locate “used” from the ‘Word Frequency List’ which opens automatically on the left side of the screen. Selecting this entry, (with ‘Collocations’ checked in the right-button mouse menu) creates a list of contexts in a right-hand window; some 181 entries in total.

Next, it is desirable to refine a little further using the collocation‘Filter’option, reducing the list to those lines containing my chosen sub-string. Adding “to_” to the filter generates a final list of 178 concordances which contain only my target search string, “used to”. By selecting ‘Export’ from the right-button mouse menu, concordances can then be exported with relative ease from within the application and opened in a word processor, ready for tabulation, (Appendix A). From a total of 1,022,828 tokens, the following frequency list is generated. Relative frequencies are out of 10,000:

Fig.1 LOB Corpus frequencies for “to”, “used” and “used to”.


Presentation, an important consideration not merely for aesthetic purposes, also demands a practical working knowledge of basic word processing operations. Ideally for beginner-level students, concordances are presented in a clear and easy to read tabular format, sorted alphabetically to enable the swift identification of collocation patterns, (Appendix A and Appendix B).

Brown Corpus

As mentioned above, the Brown corpus is accessed through the University of Pennsylvania's LDC internet site. It offers a selection of corpora for real-time analyses though access, as a ‘guest user’ is restricted to twenty days. On acceptance of the user terms and conditions, one is invited to enter the relevant search criteria in a series of selectable fields.

An initial search returns a tagged frequency list, and generates concordances for the identified search pattern. The complete list of Brown concordances is provided in their processed form, (Appendix B).

From a total of 1,189,209 tokens, the following frequency list is generated. Once again, relative frequencies are calculated out of 10,000:

Fig.2 Brown Corpus frequencies for “to”, “used” and “used to”.


Established corpora are often the culmination of a great deal of time, effort and, most significantly, money. Such investment is jealously guarded and may not, therefore, be made generally available without due considerations of costs. In some cases this may prove to be prohibitive to the less fortuitous researcher. In this light, it can be seen that the ability to access a large on-line corpus in real-time is extremely useful for those unable to avail themselves of the more traditional resources, and also appealing to those who lack the practical wherewithal necessary for the successful exploitation of a complicated text analysis program. Such corpora also offer the added benefit of speed; a list of concordances can be generated in a matter of seconds. However, at this early stage of development the on-line corpus does not yet offer the flexibility or power of a dedicated software package, such as ATA, to sort or to filter, as need dictates.


The majority of the concordances in LOB are taken up with “used to” employed to describe past situations and events. There is a visible tendency within the list to collocate with the verb “to be” and also with other common verbs:

  • as fresh as it used to be, though an
  • you herself what she used to be.
  • But then I used to be a racing
  • reading ," wrote Francis Williams,” used to be a Socialist

The corpus provides twenty-eight instances of “be used to” meaning to be “accustomed to”. The propensity is for the item to collocate with a noun or a verb, notably the gerund. Of the total number, only eleven actually occur with the gerund, which is the collocate most commonly highlighted in beginner-level textbooks. Textbooks also tend to focus on the gerund occurring after the target form:

  • time before I got used to calling them portholes.
  • Clara was used to following his lead
  • seemed to have been used to seeing couples engaged

whereas LOB offers examples of the gerund occupying a position before the target form:

  • a bit of getting used to
  • She took time getting used to the indoor lavatories

And a single instance of a noun coming between the two:

  • garage, but he was used to Grant taking his

A further significant observation is that more than half of the these concordances demonstrate collocations with the verb “get”:

  • You'll have to get used to my bad morning
  • heavy, but one got used to this

Though not the focus of this particular exercise, the list also provides some examples of the target form performing a third linguistic function, the passive voice:

  • descriptions can also be used to refer to performances
  • ratio decidendi}is normally used to refer to some
  • beggars, a term often used to describe the population,
  • ferromagnetic spinel is sometimes used to describe those ferrites

With Brown, as with LOB above, “used to” describing past events tends to collocate with the verb “to be” and other common verbs:

  • eem high, but they used to be even higher,
  • spe said, This soil used to be like that
  • ard roll. <s> This used to be part of

Also present, as noted in LOB, are instances of “used to” employed in the passive voice:

  • ma. The method used to scan the eye
  • I rand, IOCSIXG, is used to specify the second

The Brown corpus offers twelve examples of “used to” meaning to be “accustomed to”; less than half of the total number present in LOB. Of these, only five collocate with the gerund:

  • ke a little getting used to — not because it
  • ur people have been used to accepting things as
  • that must have been used to booming, `` and th
  • he governor was not used to having his integrit
  • jealous. <s> He's, used to me bringing home

    and only twoof the twelve co-occur with the verb “get”:
  • ke a little getting used to — not because it
  • little time to get, used to. After a

Possible Pedagogic Applications

In the classroom, concordances produced through the analysis of a suitable corpus can provide valuable data for the testing of existing grammatical models and practical material for the production of cloze exercises. Closer examination can also reveal patterns and constructions that may not be covered in prescribed textbooks.

The initial intent of this study was to examine the differences in usage between “used to” and “be used to”. My learners do not have a significant problem with the former, but do express confusion when attempting to differentiate it from the latter. My institution's current choice of text only instructs in the use of “be used to” co-occurring with the gerund and, consequently, my students have only been exposed to this construction in their English classes. However, the majority of these concordances in Brown and LOB occur with no gerund at all, a point worthy of highlighting in the classroom. Though different in meaning, the number of cases of “get used to” provided by the corpora, most prominently LOB, may be seen as noteworthy and also deserving of my students' attention, as this particular construction is not covered in the students' textbook at all. A practical pedagogic approach to both of these issues would be to expose my students to the corpus-generated data as part of a series of carefully coordinated lessons. Through the insights I have gained in the course of this particular study, my eventual aim would be to bring CA directly into the classroom, possibly as part of the school's regular computer studies classes, and allow my students to join the investigation as part of a hands-on practical exercise.

However, to add a note of caution, as my own small investigation reveals, there are significant differences in both frequency and usage to be found even across two very ‘similar’ corpora. It is important therefore to make only tentative inferences regarding grammatical rules or patterns of use and to acknowledge the limitations of dealing with such a small sample of data. A future piece of research conducted on a much larger text might allow for some more definite conclusions to be made.

A further possible pedagogic option, requiring an extension of this study, would be to heed the advice of Willis & Willis (1996) and Peacock (1997: 152) to produce a set of authentic materials: “materials which are used in genuine communication in the real world” (Wong, Kwok & Choi, 1995: 318), taken from a spoken, rather than written, corpus and to investigate specifically any increased signs of motivation with my less-conscientious learners.

It is perhaps a fitting conclusion to note that in the course of writing this paper a further development in the evolution of computational linguistics and the internet is reported: ICAME is now the latest in a growing number of institutions offering on-line access to all of its corpora, in this case to registered users of its commercially available CD-ROM. It seems likely that such innovations, offering increased levels of accessibility to an ever-growing body of linguistic data, will continue into the foreseeable future.


  • Biber, D., Conrad, S., & Reppen, R. (1998).CORPUS LINGUISTICS: Investigating Language Structure and Use. Cambridge: Cambridge University Press.
  • Brown University Corpus of American English.
  • University of Pennsylvania, Linguistic Data Consortium:
  • Firth, J. R. (1957). A synopsis of linguistic theory. Studies in linguistic analysis. Oxford: Oxford University Press.
  • Lancaster-Oslo/Bergen corpus (1961). International Computer Archive of Modern English. Bergen, Norway.
  • Peacock, M. (1997). The effect of authentic materials on the motivation of EFL learners. ELTJ, 51(2), 144-156.
  • Sinclair, J. (1991). Corpus, Concordance, Collocation. Oxford: Oxford University Press.
  • Stubbs, M. (1996). Text and Corpus Analysis. London: Blackwell.
  • Willis, J. & Willis, D. (1996). Consciousness-raising activities. In Willis, D. & Willis, J. (Eds.), Challenge and Change in Language Teaching. London: Heinemann.
  • Wong, V., Kwok, P. & Choi, N. (1995). The use of authentic materials at tertiary level. ELTJ, 49(4), 318-322.


Sean Maddalena holds a first degree in Law, a Diploma in TEFL and an MSc in TESOL from Aston University. Originally from the United Kingdom, he has made his home in Japan since 1989 and is currently employed by Ashiya University. His specific research interests include Course and Syllabus Design and Computational Linguistics.

Appendix A

a bit of gettingq_

used toq_ .

plane can only beq_

used toq_ a limited extent

of the man habituallyq_

used toq_ a shoulder-holster .

such computers can beq_

used toq_ advantage when a


used toq_ ask ~ * ' Has he

affluent society should beq_

used toq_ assist the less

Rolled barley isq_

used toq_ balance grass or

as fresh as itq_

used toq_ be , though an

you herself what sheq_

used toq_ be .

man myself though : Iq_

used toq_ be a { 0G.P . }

But then Iq_

used toq_ be a racing

reading , " wrote Francis Williams , "q_

used toq_ be a Socialist

done by administrative actq_

used toq_ be accomplished in

the subject Social Psychologyq_

used toq_ be called Home-making

of the May songq_

used toq_ be current in


used toq_ be fancier , but

At one time " mind * * "q_

used toq_ be identified with "

of their larger carsq_

used toq_ be made available

her hair , it neverq_

used toq_ be quite that

This lessonq_

used toq_ be read only

Sometimes that pleasant Citroenq_

used toq_ be subject to

Harry of the jointq_

used toq_ be the barman


used toq_ be three separate

I was younger Iq_

used toq_ be what is

Like heq_

used toq_ be years ago . . .

three feet long butq_

used toq_ being handled , in

of the gold filletsq_

used toq_ bind up the pŽº/span>

Miniature cedar trees areq_

used toq_ block out the

technical school ) should beq_

used toq_ broaden the youngsters '

British sources have beenq_

used toq_ calculate the effective

time before I gotq_

used toq_ calling them portholes .

I alwaysq_

used toq_ clean my rifle


used toq_ come every day


used toq_ come to Pierre's

remember a woman whoq_

used toq_ come to see

at Saintes , has beenq_

used toq_ complete the drawing

have been or areq_

used toq_ control impurity build

is what bedizened boysq_

used toq_ dance before Mogul

its phrases , especially thoseq_

used toq_ describe a visit

Kunst wasq_

used toq_ describe certain branches

with the conventional equationsq_

used toq_ describe fluxes in

unit , can be properlyq_

used toq_ describe soils in

a root that isq_

used toq_ describe the herding

as the wave functionsq_

used toq_ describe the motion

equation can indeed beq_

used toq_ describe the motion .

however , they may beq_

used toq_ describe the motions

beggars , a term oftenq_

used toq_ describe the population ,

ferromagnetic spinel is sometimesq_

used toq_ describe those ferrites

method of measurement wasq_

used toq_ determine accurately the

year group was thenq_

used toq_ determine what would

his Cambridge days , heq_

used toq_ display a corresponding

elaborate dresses than theyq_

used toq_ do .

Mould many years backq_

used toq_ do .


used toq_ do all their

strain , the two beingq_

used toq_ draw true stress /

young the Royal Navyq_

used toq_ drink it before


used toq_ drink the cheap ,

that report has beenq_

used toq_ estimate the theoretical

diametrically opposed contacts wereq_

used toq_ facilitate the observation

gouge , and the fileq_

used toq_ finish off .

the former crop beingq_

used toq_ finish off the

Clara wasq_

used toq_ following his lead ,

The method wasq_

used toq_ forecast visibility ( as

concrete tube sections beingq_

used toq_ form the sump

smoothing plane can beq_

used toq_ form the taper .

Bank years ago weq_

used toq_ get good hauls , 12

song , told me : Weq_

used toq_ get up at

This solution may beq_

used toq_ give the contribution

those places where weq_

used toq_ go .

much as Cecil Sharpq_

used toq_ go about in


used toq_ go about the

garage , but he wasq_

used toq_ Grant taking his


used toq_ hate Creedy , when

for a drink heq_

used toq_ have his grouse .

The Caxtonsq_

used toq_ have their holidays

told me " I alwaysq_

used toq_ hear a lot


used toq_ hear talk about

took time to becomeq_

used toq_ hearing so much

household possessions may beq_

used toq_ help with the

Apparently heq_

used toq_ hide it in

they may be fruitfullyq_

used toq_ His Glory .

and these can beq_

used toq_ illustrate the type

overclothe them as theyq_

used toq_ in the old

The term quasi-classical isq_

used toq_ indicate that their

growth equilibrium " paths , areq_

used toq_ investigate the stability

man , if you aren'tq_

used toq_ it , * * ' he heard

You'll getq_

used toq_ it , adorable baby .

that we should getq_

used toq_ it .

I never gotq_

used toq_ its travel-film colours

Two methods can beq_

used toq_ join the crochet

differences between jobs beq_

used toq_ justify differences in

a young man , weq_

used toq_ keep strictly to

to meet people Iq_

used toq_ know , to see

electric effect can beq_

used toq_ launch ultrasonic waves


used toq_ lie awake planning

a counter-irritant almost Iq_

used toq_ listen of nights

Marc Chagallq_

used toq_ live here and

Then that's why * - " " Heq_

used toq_ live in Tangier , "


used toq_ look * - and some

of an elephant , wasq_

used toq_ make a cake

Some separated lead-210 wasq_

used toq_ make reference standards

crochet lace can beq_

used toq_ make tablecloths , traycloths

provision which was nowq_

used toq_ make the { 0T.E .

ancient Britons , I believe ,q_

used toq_ make water hot

as it is nowq_

used toq_ mark a paragraph

Section the term wasq_

used toq_ mean something like


used toq_ mix 100 stone of

junior to Humbert , whoq_

used toq_ mock him affectionately

You'll have to getq_

used toq_ my bad morning

gauge can now beq_

used toq_ nick in the

three following winters wereq_

used toq_ obtain an independent


used toq_ organise film shows

which can then beq_

used toq_ perform an operation .

and devices to beq_

used toq_ perform the various


used toq_ play about in


used toq_ play rugger , * * ' said

lead carrier solution isq_

used toq_ prepare the reference

how Alexander the Greatq_

used toq_ recline and transact

descriptions can also beq_

used toq_ refer to performances

ratio decidendi } is normallyq_

used toq_ refer to some

it may have beenq_

used toq_ relate Christ's healing

migre * ? 2s , who notoriouslyq_

used toq_ repair to the

she said chattily , Iq_

used toq_ ride a bicycle .

and personality which journalistsq_

used toq_ ridicule , can be

the gate the cockerelq_

used toq_ run to meet

for you fellows , * * ' heq_

used toq_ say , you can

Laughable , theyq_

used toq_ say .


used toq_ say : ^ Have whatever

Of Kitchener heq_

used toq_ say with humorous

reminiscent of what weq_

used toq_ see pŽ®St .

seemed to have beenq_

used toq_ seeing couples engaged

embarrassment if she isq_

used toq_ seeing her mother

that force should beq_

used toq_ settle this problem .

the May carol heq_

used toq_ sing , with his

me the one sheq_

used toq_ sing in Kimbolton

a shaped rubber isq_

used toq_ smooth the hollow

was young schoolboy I

used toq_ sneak off to


used toq_ solve all the

the clinical weekends heq_

used toq_ spend with her .

applied , and every meansq_

used toq_ stop the train ,

in contrasting tones wereq_

used toq_ strengthen garments at

model which may beq_

used toq_ study both the


used toq_ stump round the

possibility of power beingq_

used toq_ supplement hand tools .


used toq_ take the small

and colleague , Campbell Dixon ,q_

used toq_ tell of a

The straight-edge can beq_

used toq_ test the straightness

is bought , can beq_

used toq_ the best advantage .

at ( B ) . A malletq_

used toq_ the chisel is

become ( 1 ) tired , or ( 2 ) moreq_

used toq_ the disturbance .

Soho , to get meq_

used toq_ the food , he

might as well getq_

used toq_ the idea .

they very quickly getq_

used toq_ the idea of

She took time gettingq_

used toq_ the indoor lavatories


used toq_ the snatch racket .

that most people getq_

used toq_ them .

Jane wasq_

used toq_ these sudden exigencies

or chieftain to getq_

used toq_ these trimmings because

to tinsel compliments , weq_

used toq_ think him unworldly ,

in an Embassy * - Iq_

used toq_ think it was

heavy , but one gotq_

used toq_ this .

You are not yetq_

used toq_ this sort of

decorative kale are convenientlyq_

used toq_ tone in with

horses ; they had beenq_

used toq_ trains since they

The brush contacts wereq_

used toq_ trigger off a

He oftenq_

used toq_ try to imagine

His friendsq_

used toq_ try to persuade

friend , William James , whoq_

used toq_ urge that the

in London that Jonesq_

used toq_ use in the

slaves * - everything he wasq_

used toq_ using while he

a literary province Iq_

used toq_ visit fairly often ;


used toq_ walk straight to


used toq_ walk to the

page , would have beenq_

used toq_ weigh bales of

They could beq_

used toq_ weigh several sacks

its simplest form itq_

used toq_ work in the

they are a teamq_

used toq_ working together , they

like that she hadq_

used toq_ write to me .

Appendix B

ke a little gettingq_q_

used to -- not because it

iling teasing as heq_q_

used to . <p> <s> `` Huskyq_q_q_q_

from it that sheq_q_

used to . <p> <s> `` You

little time to getq_q_

used to . <s> After a

ur people have beenq_q_

used to accepting things as

a new melody isq_q_

used to accompany his narraq_q_q_

repetitious The logical schemeq_q_

used to accomplish the formq_q_q_q_

residual hese inquiries wereq_q_

used to adjust compilationsq_q_q_ tient

uestions . <s>I 'mq_

used to all three , but

herse one hebephrenic manq_q_

used to annoy me , month

ageq_ seven-iron shot heq_q_

used to approach the greenq_q_q_q_

s> They could beq_q_

used to attack a nation '

platform and can beq_q_

used to automatically holdq_q_q_q_ iling

citiz--uglier than youq_q_

used to be , and you

ss glorious than itq_q_

used to be , it is

nistered here as itq_q_

used to be , with unleaveneq_q_q_

or less than itq_q_

used to be ? ? <p> <s>

eem high , but theyq_q_

used to be even higher '' ,q_q_q_

spe said , This soilq_q_

used to be like that

ard roll . <s> Thisq_q_

used to be part of

as e Catskills , whichq_q_

used to be the summer

that must have beenq_

used to booming , `` and th

ese profiles can beq_q_

used to calculate a temperaq_q_q_

feeli ransports that wereq_q_

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used to classify and identiq_q_q_

of materials can beq_q_

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holes and can beq_q_

used to cut exact-size discq_q_q_

the words he hadq_q_

used to defend Cromwell . <q_q_q_ he

grea emical methods wereq_q_

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used to derive a general

was a Spanish wordq_q_

used to describe cattle ofq_q_q_q_

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used to describe felt humanq_q_q_

integritq_ ind words travelersq_q_

used to describe Little Rocq_q_q_

prbody temperature isq_q_

used to describe the radiatq_q_q_

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used to destroy other mobilq_q_q_

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used to detect submarines ,q_q_q_ ma . <

the the anonymous Womanq_q_

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each time as heq_q_

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used to equate symbolic namq_q_q_

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used to fasten them to

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used to frustrate the citizq_q_q_q_ --

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he governor was notq_

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and had already becomeq_

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eem strange to earsq_q_

used to hillbilly and jazz

and he was notq_q_

used to horseback . <s> Now

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used to illustrate anotherq_q_q_q_q_ power

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used to indicate a municipaq_q_q_q_ **

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used to keep the wastes

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cereal aining appliance isq_q_

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c. <s> The Presidentq_q_

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by the same methodq_q_

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used to make candles in

as urposes -- also areq_q_

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out ''surpluses had beenq_q_

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used to provide the dryingq_q_q_q_

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most of what weq_q_

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ma . <s> The methodq_q_

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stem . <s> DIOCS isq_q_

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me rand , IOCSIXF , isq_q_

used to specify the first

I rand , IOCSIXG , isq_q_

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erb garden was alsoq_q_

used to stop bleeding , andq_q_q_

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used to store cumulative req_q_q_q_

Throu was constructed andq_q_

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corrosion e been successfullyq_q_

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than to an Americanq_q_

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pirical data can beq_q_

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sort of thing thatq_q_

used to take place in

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used to tell me , `` When

South nt this opportunityq_q_

used to tell them about

ygous Af cells wereq_q_

used to test each sample ;q_q_q_q_

invento <s> Where Americansq_q_

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unt of a machine-familyq_q_

used to this very day

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was a trick theyq_q_

used to try and conceal

San Juan , but Iq_q_

used to work on a

Appendix C

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