APHRICA: A PHrase In Context Algorithm

  1. 1. John L. Dawson

    Literary and Linguistic Computing Centre - Cambridge University

Work text
This plain text was ingested for the purpose of full-text search, not to preserve original formatting or readability. For the most complete copy, refer to the original conference program.

APHRICA: A PHRase In Context
This paper was in part inspired by a talk given at
the ALLC/ACH92 conference at Oxford by Ian
Lancashire. His talk was entitled “Phrasal Repetends in Literary Stylistics” and included the remarks:
Phrasal repetends also increase in complexity combinatorially as they grow longer. For
example, every 5-fixed-word repetend occurring 7 times contains 9 smaller fixed subphrases as well as a larger number of twoword, three-word, and four-word unfixed
(collocating) combinations also occurring at
least 7 times. (Any of these sub-phrases may
occur more than 7 times, depending on the
text.) Any phrasal repetend larger than two
words, as a result, sits on the top of a pyramid
of other phrasal repetends.
He also commented that a program searching any
text for all possible collocations of a certain degree
of significance appears to be computationally demanding. This is a consequence of the combinatorial effect mentioned above. Certainly, extracting
all general repeated collocations from a text would
be extraordinarily time-consuming, so the present
paper limits itself to the problem of extracting all
repeating fixed phrases and sub-phrases, where
the words concerned are adjacent.
The program Tact [1], which is widely available,
provides some of the facilities for achieving this
kind of analysis.
Figure 1 shows part of a key-word-in-context concordance to T. S. Eliot’s plays [2, 3], sorted by
right-context to show repeating phrases, and the
frequencies of phrases and sub-phrases which can
be derived from this. It is quite clear that there are
several such phrases, and that phrases longer than
two words contain sub-phrases which themselves
may occur more often than their parent phrases.
The APHRICA Algorithm
Looking at key-word-in-context concordances gives the clue to extracting all possible repeated
phrases, and the method is expressed as an algorithm below.
(1) Make a concordance of all words which appear only once in the text. The context of the
word is not of interest and may be discarded;
what is required is the word and the reference
showing the line on which it appears.
(2) Sort the headword/reference pairs back into
their original textual order.
(3) Convert the sorted headword/reference pairs
into editing commands which replace the singly-occurring words by some non-alphabetic
symbol such as <>. A singly-occurring word
can obviously not form part of a repeating
(4) Replace those punctuation marks which are
not to be included within repeated phrases by
<> as well. Replace multiple <> by a single
<>. Extract the sequences of words occurring
between <> as single lines. This divides the
text into variable-length sections which comprise the longest possible repeating phrases.
(5) Make a keyword-in-context concordance sorted by right-context, but with no left-context.
(6) Because of the way in which the concordance
has been sorted, any phrase A B C which
appears sorted under the word A will also
produce the phrase B C sorted under the word
B, and this solves part of the problem of combinatorial effects mentioned at the beginning.
Now for any three lines of this concordance,
X, Y, and Z, we need a program which for line
Y outputs
longest-match ( longest-match ( X,Y ),
longest-match ( Z,Y ) )
working in whole words only, starting from
the left. Any output line which then consists
only of a single word can be discarded, as in
that particular line of the concordance it does
not form part of a repeating phrase.
(7) Process the resulting set of repeating phrases
as follows: for any phrase which contains
more than two words, output the phrase itself
and all possible sub-phrases which contain
two or more words, again starting from the
left. Thus the phrase A B C D would be output
together with the sub-phrases A B C and A B.
(8) Make an alphabetic frequency list of the resulting phrases and sub-phrases.
These steps are certainly time-consuming in computational terms, especially the concordance steps
(1) and (5), but it is exactly those steps which
reduce the processing time in later stages. The
same technique, with suitable modifications,
could be used on lemmatized or otherwise normalized texts, or on a grammatical coding of a text.
Using the Repeated Phrases List
One obvious technique to try with the alphabetic
frequency list of phrases is to construct a frequency distribution.
Plotting the absolute frequency of n-word phrases
is not very informative. We know, by its very
nature, that any n-word phrase with frequency f
must contain two phrases of length (n-1) words,
each with frequency greater than or equal to f, and
so on iteratively. In particular, an n-word phrase
with frequency f will contain (n-1) two-word phrases with frequency at least f.
A more interesting statistic is the ratio of the
frequency of (n-1)-word phrases to that of n-word
phrases. If this ratio is very low for all values of n,
the implication is that most repeated phrases are
contained in longer repeated phrases, but do not
occur separately to any great extent. In other
words, the author tends to write in relatively long
phrases and avoids the standard juxtapositions of
function words which are inherent in most texts.
Such a text is likely to resemble (or be) poetry,
where the constraints of normal sentence construction are considerably relaxed. It seemed to me
that a good test of this would be to apply the
method to T. S. Eliot’s poetry and plays, because
the plays themselves are by no means in standard
prose, and abound with poetic features. It turns out
that the patterns of phrase frequency ratios are
indeed sufficiently different to mark the distinction between Eliot’s plays and his poetry.
Examples will be shown of the results of applying
these techniques to the poetry and prose of Robert
Graves and T.S. Eliot.
[1] John Bradley, “TACT Design”, in T.R. Wooldridge (ed.), A TACT Exemplar, CCHWP 1
(Toronto: Centre for Computing and the Humanities), pp. 1–4.
[2] T.S. Eliot, The Complete Poems and Plays of
T.S. Eliot (London: Faber and Faber, 1969).
[3] J.L. Dawson, P.D. Holland, & D.J. McKitterick (eds), A Concordance to “The Complete
Poems and Plays of T.S. Eliot” (Ithaca: Cornell University Press, 1995).

If this content appears in violation of your intellectual property rights, or you see errors or omissions, please reach out to Scott B. Weingart to discuss removing or amending the materials.

Conference Info

In review


Hosted at University of Bergen

Bergen, Norway

June 25, 1996 - June 29, 1996

147 works by 190 authors indexed

Scott Weingart has print abstract book that needs to be scanned; certain abstracts also available on dh-abstracts github page. (https://github.com/ADHO/dh-abstracts/tree/master/data)

Conference website: https://web.archive.org/web/19990224202037/www.hd.uib.no/allc-ach96.html

Series: ACH/ICCH (16), ALLC/EADH (23), ACH/ALLC (8)

Organizers: ACH, ALLC