Tagging Time in PROLOG: from quick and dirty to TEI

Tagging Time in PROLOG: from quick and dirty to TEI

Jan
Christoph
Meister

University of Hamburg
jan-c-meister@uni-hamburg.de

2003

University of Georgia

Athens, Georgia

ACH/ALLC 2003

editor

Eric
Rochester

William
A.
Kretzschmar, Jr.

encoder

Sara
A.
Schmidt

This paper presents work in progress from a current research project at Hamburg
University that employs Humanities Computing methodology for developing and
testing a new theory and model of “narrative time”. Our premise is that
narrative time should be defined in functional and not in essential or
categorical terms: time is not an objective phenomenon, but a cognitive
construct and can thus best be modeled in terms of a 'temporality effect'. This
effect -- that is, the impression of temporal order in narrative, both on the
level of fictional reality and narrative discourse – is to be explained and
analyzed in terms of the distribution of empirical 'notions' (representations of
objects) and 'temporal operators' throughout a representational medium, in our
case: a narrative text.
Humanities Computing methodology plays a central role with regard to both the
description (markup) and the subsequent combinatory analysis of relevant textual
elements. However, adhering to a TEI compliant tagging approach proves
unacceptably complicated. The paper therefore argues for a quick and dirty approach to time tagging based on feature structure
tags that are defined in the form of PROLOG clauses.

THEORY
To date most theories of narrative—in particular those focusing on the domain of
literary narratives—conceptualize of ‘time’ in terms of a dichotomy of narrated time vs. time of
narration or, as Günter Müller’s classic formulation goes, of Erzählzeit vs. erzählte
Zeit. This is essentially an ontological distinction that attempts to
set apart two ‘worlds’, each of with is seen to have its ‘own time’. However,
this distinction immediately becomes problematic when dealing with non-fictional
representations of events which, irrespective of chronological proximity, are by
definition situated on a singular objective time line. Our approach is therefore
based not on the traditional narratological concept, but rather on the unitary
model of time originally proposed by McTavern who distinguished between two
perspectives onto time: namely, that of events
in an objective before-after relationship (the
so-called B-series of time), and that of events as
occurring in the subjective cognitive order of future-present-past (A-series).

COMPUTER-BASED IMPLEMENTATION
As far as tools are concerned, the implementation of this theoretical model in a
Humanities Computing orientated project has necessitated the development of two
programs:
TempusMarker -- a software tool providing automatic and semi-automatic
markup routines for the tagging of temporal expressions in natural
language texts. A prototype of TempusMarker has already been
programmed.Available for download at . A
detailed description of the tool (in German) is
included.
TempusParser -- an analytical tool that generates a version (or
versions, as the case may be) of the base text in which all the
sequences that form a complex narrative discourse are organized in
strict chronological order. This (re)construction is the result of an
algorithm driven process of analysis and recombination of textual
segments during which the ‘time stamp’ of each segment as indicated by
the temporal tags is interpreted.A schematic representation
of the TempusParser architecture and workflow is available at

The computational implementation of McTavern’s model for the purpose of concrete
analyses of A-series governed textual discourse and its eventual reconstruction
in terms of B-series ordered event sequences offers an interesting example for
the difficulties faced by the computing Humanist who tries to tackle even
modestly ‘intelligent’ hermeneutic problems. In the project to be presented here
an added problem stems from its empirical orientation: rather than having
experts (Literary Scholars) tag the texts we are using student groups in order
to simulate as closely as possible the ‘naïve’ reader’s processing habits. A
demonstration of the actual tagging process, including the use of the
TempusMarker prototype, will form part of the presentation.
The computational implementation of McTavern’s model for the purpose of concrete
analyses of A-series governed textual discourse and
its eventual reconstruction in terms of B-series
ordered event sequences offers an interesting example for the difficulties faced
by the computing Humanist who tries to tackle even modestly ‘intelligent’
hermeneutic problems. In the project to be presented here an added problem stems
from its empirical orientation: rather than having experts (Literary Scholars)
tag the texts we are using student groups in order to simulate as closely as
possible the ‘naïve’ reader’s processing habits. A demonstration of the actual
tagging process, including the use of the TempusMarker prototype, will form part
of the presentation.
Whereas the temporal value of the respective natural language expressions -- be
they denotative or deictic -- is comparatively easy to establish either
contextually, or from a dictionary, their explication in the form of
standardized TEI markup (core tag set + additional tag sets for dates and time,
ref. chapter 20.4. of TEI guidelines) has proven rather unwieldy and often
contra-intuitive to our readers. Defining more readily comprehensible feature structure tags would seem to be the
alternative of choice; however, this raises the methodological question of how
to design a sufficiently fine-grained feature structure that does not
automatically become completely idiosyncratic to the particular research problem
at hand, thus inadvertently restricting the uses of the tagged corpus at a later
stage.
Against this background the paper advocates and will demonstrate a calculated
quick and dirty approach to designing temporal
feature structure tags. In particular, it will be shown how the PROLOG predicate
structure can facilitate rapid prototyping of feature structure tags.

CONCLUSION
Expressing relatively complex hermeneutical problems and models in terms of
Humanities Computing methodology and standards should be conceived of as a
process of translation, rather than one of mere re-presentation. From a
hermeneutical point of view semantic tags are not
just descriptors, but rather predicates of a prepositional clause in which the
tagged string itself is one argument, and its feature values the subsequent
arguments. Capturing experimental temporal feature structure tags in the form of
PROLOG predicates therefore holds two advantages: first, it offers a more
intuitive approach to semantic tagging. Second, it facilitates automatic
conversion of feature structures into composite TEI tags at a later stage, thus
turning the quick and dirty into the beautifully
intricate -- and fast at that.

REFERENCES

Christopher
Habel

Frank
Schilder

From Temporal Expressions to Temporal Information:
Semantic Tagging of News Messages

- 27.11.2002

Günter
Dammann

Jan
Christoph
Meister

The temporality effect: Design and computer-based
application of a constituent model of narrative temporal
order

- 27.11.2002
(contains hyperlinks to the prototype of the TempusMarker tagging
tool.)

John
Ellis
McTaggart

The Unreality of Time

Mind

17

457-474
1908

Günther
Müller

Erzählzeit und erzählte Zeit

Festschrift für Paul Kluckhohn und Hermann
Schneider

Tübingen

1948
195-212

TEI Consortium

C.
M.
Sperberg-McQueen

Lou
Burnard

TEI P4 - Guidelines for Electronic Text Encoding and
Interchange
XML-compatible edition

2001

(Chapter 6.4: Names and Dates, and Chapter 20.4: Names, Numbers,
Dates, Abbreviations, and Addresses.)