Computational Generation of Limericks

Computational Generation of Limericks

Greg
Lessard

Queen's University
lessardg@qsilver.queensu.ca

2003

University of Georgia

Athens, Georgia

ACH/ALLC 2003

editor

Eric
Rochester

William
A.
Kretzschmar, Jr.

encoder

Sara
A.
Schmidt

FOREWORD

A program called VINCI from Queen's
Employs computational means
To make metre and rhyme
In right to left time
So limericks appear on your screens.

The people attending this session
We hope will have gained the impression
That these powerful tools,
With appropriate rules,
Can give rise to poetic expression!

BACKGROUND
There is evidence that the generation of at least some classes of humour is a
rule-governed activity, formalisable in terms of algorithms, and
implementable computationally in order to generate actual humorous
utterances. In earlier work, using the VINCI natural language generation
environment, we have shown this to be the case for several subclasses of
verbal humour, including Tom Swifties and several classes of riddles. (See
Lessard & Levison, 1992, 1993, 1995, 1997). Others have done similar
work (see for example Binsted & Ritchie, 1997). This does not mean
that we suppose the specific algorithms used in generation to exist as
internal mental representations in speakers, but only that the productions
observed in humans admit of formalisation.
It must be admitted, however, that puns and riddles form instances of what is
often called verbal humour. This is typically non-narrative, based on
relatively simple paradigmatic lexical relations, and usually evaluated in
terms of cleverness rather than funniness. (See Lessard, Levison &
Venour, 2002, for a discussion of the distinction.) Instances of verbal
humour are in many respects inherently simpler than more narrative
structures like jokes. Limericks, on the other hand, presuppose at least a
primitive narrative structure. As such, they provide a useful proving ground
for more advanced work on both language generation (since it is necessary to
take account of textual coherence) and humour generation (since narrative
structure is involved).

LIMERICKS
Limericks may be characterised generally as five-line verses with the aabba
rhyme scheme, one of a range of metrical foot structures, and some attempt
at humour or at least cleverness. (For discussion, see Bibby, 1978). A
typical example will illustrate the model:

There was an old man from Peru
Who dreamt he was eating his shoe
He awoke with a fright
In the midst of the night
And found it was perfectly true.

Taken as a subset of more general poetic language, limericks confront us with
a number of practical problems, but also with a number of theoretical
challenges when they are compared with prose-based natural language
generation. For example, traditional approaches to text planning and
generation tend to be driven by conceptual and syntactic rather than
metrical structure. This is unsurprising when one considers that the object
of most systems of the sort is to represent some encyclopedic or
data-base-like description of some state of affairs in a discursive format.
In such a context, the primary factors to be considered include the model of
the user (see for example Paris, 1993), the overall structure of the text
plan (see for example McKeown, 1985), paragraph-level phenomena (see for
example Mann, 2002), and problems of reference (see for example Dale,
1992).
As a consequence, planning tends to be top-down (from universe of discourse,
to dialogue model, to context, to overall text, to paragraph, to sentence)
and many of the phenomena to be dealt with (anaphora, for example) can be
examined in a left-to-right sequence. This has meant that conceptual tools
such as phrase structure grammars or their variants have provided sufficient
power to deal with the problems raised. Even phenomena such as freer word
order may be captured in such systems by means such as the splitting apart
of linear precedence and immediate dominance as in formalisms like
Generalized Phrase Structure Grammar (Gazdar et alii, 1985).
The production of poetic text, on the other hand, requires that content be
filtered by metrical and phonological factors such as the number of
syllables, stress, and rhyme. A particularly interesting consequence of this
fact is that generation must take account of the ends of lines in the
production of the beginning and middle. For example, in the case of the
limerick quoted above, we may represent the syllable structure as follows,
where s represents an unstressed and S a stressed syllable:
It can be seen that the first, second and fifth line contain an iamb followed
by two anapests, while the third and fourth lines contain two anapests. In
addition, rhyming lines (Peru-shoe-true) must end on the same stressed
syllable nucleus and coda (to use the terminology of metrical phonology (see
for example Hogg, 1987). Note that these are not necessarily lexical items:
in the first, second and fifth lines, the sequences “his shoe” and “-ly
true” rhyme with “Peru”.

GENERATION
A full analysis of the semantic, syntactic, lexical and phonological
relations found in the limerick would take more space than is available
here. However, from the generative perspective, it is possible to imagine
three mechanisms to satisfy this constellation of constraints:
1. exhaustive generation: in essence, if we define a set of
templates, we can generate large numbers of instances of potential
limericks and ask a human to select those few judged to be of good
quality. (This is the monkeys typing Shakespeare model, or Borges’
library.)
2. initial generation followed by tweaking: we may also begin by
producing a sequence of lines and then selectively edit these to
approach the target of an acceptable limerick, by means of the
addition, removal or shifting of items. This may be how human poets
work: it is how we produced the limericks at the head of this
abstract. (Valéry is said to have claimed that the first line of a
poem was a gift of the gods and that the remainder was the product
of the poet's craft and efforts.) Since the edit operations
described above are well-known in the computational context, it is
not impossible to imagine their implementation.
3. right-to-left generation: given the direction of the
constraints in limericks, a possible computational model involves
the selection of the right-most elements of a sequence of lines as a
starting point and then within each line, the
constraint-satisfaction generation of the intervening elements
required to flesh out the entire limerick.

In fact, these right-to-left formal constraints must interact with top-down
constraints which govern the semantic coherence of the text. In other words,
in order for the limerick to be coherent, the narrative events which it
includes must be consistent with the subject. These thematic constraints may
be fairly loose, as in the Old Man from Peru poem, where there is no
particular logic which attaches old men from that part of South America and
the ingestion of footwear (although more generally, the poem respects the
constraint that old men are humans and that humans eat food which is a
subset of tangible objects, and that footwear is also a subset of tangible
objects). On the other hand, they may be quite tight, as in the VINCI
limericks, which capture a set of characteristics of the software (its
origin, the architecture of the program). Compare as well Bibby’s attempts
to produce limericks appropriate to each of the Cambridge colleges.
The limerick thus represents the semantic expansion from one or more initial
lexical choices, by means of the selection of traits or actions which are at
least consistent with these. This presupposes a rich representation of the
characteristics of each lexical item, including both high-level semantic
traits such as that between humans, eating and objects, but also more
encyclopedic ’information, such as the fact that VINCI is a program produced
at Queen's. (See Peeters, 2000 for a discussion of some of the problems
found at this ‘lexicon-encyclopedia interface’). Note also that a
sufficiently rich set of traits will provide the seed for variant limericks
based on the same starting point. Consider for example the following example
by Edward Lear:

There was an Old Man of Peru,
Who watched his wife making a stew;
But once by mistake,
In a stove she did bake,
That unfortunate Man of Peru.

At the formal level, problems arise both between lines (rhyme) and within
lines (metrical structure). Consider the latter in the context of the
initial old man from Peru poem. Let us assume that we have determined to use
a metrical structure based on an iamb and two anapests and that we have
selected the the place-name Peru. At this point, we have used up two of the
eight available syllables. We also know that the next earliest syllable must
be unaccented. The solution found here is “from”. At this point, we know
that we have a prepositional phrase “from Peru” which requires (among other
choices) a noun phrase with the appropriate accent structure. This
constraint is satisfied here by “an old man”). However, in order to verify
that this noun phrase is appropriate, we must have knowledge of its metrical
structure. For example, if the target were an iamb, we would need to seek,
among other possibilities, a DET N structure. This application of
constraints cascades right to left until the overall metrical target is met,
within the semantic constraints already specified

IMPLEMENTATION
In the conference presentation, we will illustrate the implementation of the
approach described above using the VINCI natural language generation
environment (see for
details). Briefly, VINCI allows for the initial specification (PRESELECTION)
of a constellation of lexical items which may be constrained by semantics,
morphological and syntactic characteristics, and phonology. Preselected
items, as well as all their characteristics, are available to subsequent
steps of the generation process. Among other things, this allows for
multiple layers of preselection, in which a first item determines a set of
rhyme constraints, as well as a set of semantically appropriate
elements.
Within each line of the limerick, and between lines, the VINCI mechanism of
GUARDED SYNTAX allows the control of subsequent steps of the overall
generation to be conditioned by the framework existing at that point. (A
simple example of guarded syntax: if a noun phrase node carries the
attributes ‘first person’ or ‘second person’, then its children may only be
instantiated by a pronoun, whereas if the parent node carries the attribute
‘third person’, then the children may be pronouns, full noun phrases, or
proper names.) Applied to the production of a limerick, and assuming
right-to-left generation, if the parent node of a tree contains a
prepositional phrase which sums to an anapest, then the next left-most chunk
of syntax must inherit this information and construct an appropriate item
from a library of possible patterns.
One consequence of this model is that syntax is reduced from a single
overarching tree to the sum of a number of possible micro-trees. Such an
approach is comparable to the model of Tree Adjoining Grammars, in which
insertion and development occurs at the level of lexical-based subtrees (see
Joshi & Schabes, 1997). It is also somewhat similar to the Labelled
Deductive System approach used in parsing by Kempson et alii, 2001. Another
consequence is that by precluding tweaking and editing, the system itself is
forced to deal with the interplay of linguistic levels and constraints,
without human assistance, thus providing an acid test for both the model and
the implementation. Of course, this leaves aside the question of evaluation,
itself a thorny issue, since the criteria used are many, varied and probably
fuzzy as well. In related work, we are examining the ability of humans to
learn how to produce limericks, as well as their ability to evaluate
them.

REFERENCES

Harold
Cyril
Bibby

The Art of the Limerick

Hamden, Conn.
Archon Books
1978

Kim
Binsted

Graeme
Ritchie

Computational rules for punning riddles

Humor

10
1
25-76
1997

Robert
Dale

Generating referring expressions: constructing
descriptions in a domain of objects and processes

Cambridge, Mass.
MIT Press
1992

Ruth
Kempson

Wilfried
Meyer-Viol

Dov
Gabbay

Dynamic Syntax: the Flow of Language
Understanding

London
Blackwell
2001

G.
Gazdar

E.
Klein

G.
Pullum

I.
Sag

Generalized Phrase Structure Grammar

Cambridge, MA
Harvard University Press
1985

Richard
Hogg

Metrical phonology: a coursebook

Cambridge
Cambridge University Press
1987

A.
K.
Joshi

Y.
Schabes

Tree-Adjoining Grammars

G.
Rozenberg

A.
Salomaa

Handbook of Formal Languages

Vol. 3
Berlin
Springer
1997
69-124

Greg
Lessard

Michael
Levison

Chris
Venour

Cleverness versus funniness

April Fool’s Day Workshop on Computational Humour,
Trento

2002

Greg
Lessard

Michael
Levison

Rule-governed wordplay and creativity

Mind II: Computational Models of Creative
Cognition

Dublic City University
1997

Greg
Lessard

Michael
Levison

Linguistic and Cognitive Underpinnings of Verbal
Humour

International Cognitive Linguistics Association
Conference, Albuquerque

1995

Greg
Lessard

Michael
Levison

Computational Modelling of Riddling Strategies

ACH/ALLC Joint Annual Conference, Georgetown
University, Washington, DC

1993

(Extended abstract in conference proceedings, pp. 120–122.)

Greg
Lessard

Michael
Levison

Computational Modelling of Linguistic Humour: Tom
Swifties

ALLC/ACH Joint Annual Conference, Christ Church,
Oxford

1992

(Extended abstract in conference proceedings, pp. 175–178.)

W>
Mann

RST Web Site

2002

Kathleen
McKeown

Text generation : using discourse strategies and focus
constraints to generate natural language text

Cambridge
Cambridge University Press
1985

Cécile
Paris

User modelling in text generation

London
Francis Pinter Publishers
1993

Bert
Peeters

The Lexicon-encyclopedia interface

New York
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2000