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{{Paper
|id=Vol-2455/paper1
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|title=Speaking of Location: Communicating about Space with Geospatial Natural Language
|pdfUrl=https://ceur-ws.org/Vol-2455/paper1.pdf
|volume=Vol-2455
|authors=Kristin Stock,Christopher Jones,Thora Tenbrink
|dblpUrl=https://dblp.org/rec/conf/cosit/StockJT19
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==Speaking of Location: Communicating about Space with Geospatial Natural Language==
https://ceur-ws.org/Vol-2455/paper1.pdf
Speaking of Location: Communicating about
Space with Geospatial Natural Language
Kristin Stock
Massey Geoinformatics Collaboratory, Massey University, Auckland, New Zealand
k.stock@massey.ac.nz
Christopher B. Jones
School of Computer Science and Informatics, Cardiff University, Cardiff, United Kingdom
jonescb2@cardiff.ac.uk
Thora Tenbrink
School of Languages, Literatures and Linguistics, Bangor University, Bangor, United Kingdom
t.tenbrink@bangor.ac.uk
Abstract
Speaking of Location 2019 is the second edition of the Speaking of Location workshop series, which
aims to foster transdisciplinary research to address the problem of automatic interpretation and
generation of geospatial natural language. This introduction to the workshop proceedings provides
background, discussing the definition and nature of geospatial natural language, presenting the
papers contained in the proceedings volume, and situating them within the theoretical framework of
The Semantic Pyramid, which is also described.
2012 ACM Subject Classification Artificial Intelligence → Natural Language Processing; Spatial-
temporal systems → Geographic information systems
Keywords and phrases geospatial natural language, locative expressions, geographic information
retrieval
1 Introduction
Speaking of Location 2019 was the second edition in the Speaking of Location workshop
series, the first having been held in l’Aquila, Italy in 2017. Both workshops were held in
conjunction with the long-running Conference on Spatial Information Theory. Speaking of
Location workshops bring together researchers from across several disciplines, all of which
have understanding that is needed to achieve the automatic generation, extraction and
interpretation of natural language descriptions of geographic space. Linguistics researchers
bring an understanding of the nature of language that describes location, and the way it
is used in different cultures. Cognitive Science researchers bring an understanding of the
ways that people conceptualise the world, particularly the geographic world, including the
elements within it, and the way in which location is understood. Geography researchers
bring an understanding of the geographic world itself, and the different ways in which it
may be viewed, depending on purpose and environment. Computer Science researchers
bring methods and theory that may be applied to automation of the complex and nuanced
ways in which we describe location. All of these disciplines, and others, are required for
the realisation of the vision of a system that can understand and generate human language
about location in the way that humans do. Speaking of Location workshops are intended to
facilitate, enable and encourage steps towards this vision.
In the following introduction to the workshop proceedings, we provide a brief outline of
geospatial natural language and its complexities, before providing a conceptual framework
(The Semantic Pyramid) and overview of the presented papers.
Copyright © 2019 for this paper by its authors.
Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0)
In Proceedings Speaking of Location 2019: Communicating about Space, Regensburg, Germany, September-2019.
Editors: K. Stock, C.B. Jones and T. Tenbrink (eds.);
Published at http://ceur-ws.org
2 Speaking of Location 2019
2 What is Geospatial Language?
Humans routinely describe location using natural language. While locations are often
described using place names, the use of terms and constructions that describe the location of
an object relative to another is also common (e.g. the church is opposite the bridge or the
gardens are beside the Waikato River). Such expressions can be very complex, containing
multiple nested clauses and different reference frames. Thus location may be described
relative to the observer, relative to another object (its location or its intrinsic properties)
or relative to an external reference frame [9]. They may describe the location of an object
as a static relationship to another object (as in the examples above), or dynamically using
directions, focusing on how the location could be reached from some other location. In all
cases, various perspectives can be used, such as the observer’s perspective (static: the shop
is left of the church from my point of view, dynamic: you’ll pass the shop on your left),
object property based (the shop is in front of the castle entrance), or compass-based (the
shop is north of the church). Compass-based perspectives are often associated with survey
perspectives, whereas observer’s perspectives are commonly used in route descriptions [14].
A typical location description consists of three elements: the object whose location is
being described (known as the locatum, figure or trajector), the object that is used as a
reference (known as the relatum, ground, landmark or reference object), and the relationship
between them, known as the spatial relation [9, 13, 8]. Spatial relations may take many
forms [15], ranging from the very simple preposition (beside, opposite, near) to much more
complex expressions in which verbs, adverbs, syntactic devices like commas or apostrophes
and/or multi-word phrases also carry spatial information (for example, the road continues
north beside the river, turning west where the river divides).
3 Communicating about Space across Different Contexts and
Purposes
Context is a key element in the correct interpretation of natural language descriptions of
location. Location descriptions may be made in different contexts, and for different purposes,
and these have an impact on the way in which location descriptions are understood, and the
degree of precision in our interpretation of the description. For example, the expression the
church is opposite the bridge may be interpreted differently depending on the specific scene.
Figure 1 shows two possible scenes that could be considered consistent with this expression,
but that show quite different configurations. Thus if we don’t have other details about the
scene, there are often a number of different ways an expression could be interpreted, due
in part to contextual factors, but also the tendency for natural language expressions to
accommodate vagueness and underspecificity [1].
The way expressions are interpreted may also vary depending on what is possible or likely.
For example, the preposition on has many senses [2], and we interpret the correct sense in
part by considering what is the most likely, given the kinds of things we know about the way
the environment is structured and what we are likely to encounter. For example, Mary lives
on the island implies that Mary’s house is physically on the surface of the island [5, 7, 3, 10],
but this interpretation of the preposition on is not likely for the expression Mary lives on
the main street, because houses are rarely built directly on the surface of the street itself.
In contrast, we interpret this to mean that Mary’s house is on the side of the main street,
facing on to it. Conversely, this interpretation would not work for Mary lives on the island,
as Mary would then live in the water (unless Mary lives in a house boat, but then we would
Kristin Stock, Christopher B. Jones and Thora Tenbrink 3
Figure 1 Example Interpretations of the church is opposite the bridge
be likely to use a different expression altogether).
4 The Semantic Pyramid
The well-known Semantic Triangle [11] (Figure 2) de-
scribes the relationship between Referents (real world
objects and situations); Thoughts (human conceptu-
alisations of them, which reflect the cognitive model
that humans hold in their minds for those objects) and
Symbols that we may use to represent them (e.g. nat-
ural/human language). This framework describes the
relationship between objects and their cognitive and
symbolic representations. As well as natural language,
symbolic representations may include those in digital
form, and while in the standard semantic triangle,
these would be accommodated under the Symbols
corner of the Triangle, here we present an expanded
version of the Semantic Triangle that draws attention
to the more specific details of digital representations
of language and knowledge that are important for the Figure 2 The Semantic Triangle
task of interpretation and generation of geospatial
natural language, and is illustrated in Figure 3. We
create an additional triangular face, defined by two additional corners, one of which reflects
the digital representation of natural language: the Language Representation corner. In
order to work with geospatial natural language in computers, we transform it into a more
structured form, extracting the elements that are important for the task of interpreting
language. This may include the elements described in Section 2 (locata, relata, spatial
relation), but may also include other related items like frame of reference. For example, [6]
4 Speaking of Location 2019
extract trajector, landmark and spatial indicator. The relationship between the Symbols
(natural language) corner of the Semantic Pyramid (which formed a corner of the original
Semantic Triangle) and the new, Language Representation corner, involves a process of
abstraction, the former being the natural language that humans use, and the latter being
a structured form of the pertinent elements that a machine can work with. The second
new corner that appears in the Semantic Pyramid but was not in the Semantic Triangle, is
that of knowledge representation, in which a computer stores a digital representation of a
human conceptualisation. This might consist for example of a model of geographic space that
encodes the way that entities in space relate to locations on earth and to each other as in the
case of raster or vector representations, which reflect two different ways of conceptualising
space; a domain ontology, which encodes the categories that communities use to describe the
world and which reflect a common conceptualisation; and a logical formalism that supports
reasoning about relations in geographic space (e.g. RCC8 [4]). Ontologies that are abstracted
from natural language like GUM-Space [1] and ISO-Space [12] exist somewhere on the edge
that joins the Language Representation corner to the Knowledge Representation corner, in
that they vary in how closely they attempt to model human conceptualisations in contrast
to their linguistic representation.
Figure 3 The Semantic Pyramid
In combination, the corners of the Semantic Pyramid reflect the range of research addressed
by the Speaking of Location 2019 Workshop. We need to engage with these various fields
of study in our efforts to adequately and comprehensively address the task of automated
interpretation and generation of natural language location descriptions. Doing so requires
input from a number of disciplines. In order to perform the interpretation and generation
Kristin Stock, Christopher B. Jones and Thora Tenbrink 5
task, we need to understand how people conceptualise geographic objects, and this requires
work in cognitive science and spatial cognition. We also need to understand the ways in
which people use spatial language to describe the world, and particularly spatial scenes, and
this requires the expertise of linguists. To identify, extract and represent relevant elements
from language in a digital format, the expertise of linguists, computational linguists and
computer scientists are required in combination. To identify, extract and represent relevant
conceptual knowledge in a system to enable automated interpretation and generation, the
expertise of computer scientists, working with cognitive scientists and geographers, is needed.
Ultimately, the boundaries between these disciplines blur and hence a combined effort is
required to address the challenge. This is the purpose of the Speaking of Location Workshop
series. In 2019, in addition to a tutorial on Cognitive Discourse Analysis [16], position
pitches, a keynote and a panel discussion, we included 8 research papers in the workshop
and the proceedings. These papers occupied different locations on the corners and edges of
the Semantic Pyramid.
Clustered around the Symbols corner of the pyramid are papers that focus on the nature
and characteristics of spatial language, including Keerthana’s paper, which describes the
nature of boundedness in path descriptions in the Mayalayam language, and then looks
at how this is related to paths that are stratified (consist of multiple segments); Palmer,
Blythe, Gaby, Hoffmann and Ponsonnet who discusses the use of frame of reference
in Australian Aboriginal languages, calling into question the common view that absolute,
cardinal direction-focused frames of reference are dominant in these languages, and revealing
a strong link to landscape. These papers focus on the nature and understanding of spatial
language per se, rather than automation, but are useful for the project of interpreting and
generating geospatial natural language in that they help us to understand the ways in which
people use spatial language, and which we therefore need to consider when attempting to
automate interpretation or generation of location descriptions. These cross-linguistic studies
also help us to understand the range of variations that are possible between languages,
understanding that is essential for the creation of automated systems that can be used in a
multi-lingual environment.
Also focused on the understanding of spatial language (Symbols corner) is Richard-
Bollans, Gómez Álvarez, Bennett and Cohn, which describes a tool that is designed to
collect data to enable examination of the ways in which people understand spatial relations;
and then provides analysis of data collected using that tool and Bae, who presents a
paper that discusses the narratives that are used during joint route planning, applying a
Conversation Analytic framework to study the structure of the interactions. Bahm combines
a focus on wayfinding with that on a specific spatial relation: through, identifying three
types of relationships between the through preposition and the scene within which it is
applied, in a museum environment. Again, the focus of this work is at the Symbols corner
of the pyramid. Moving around the base of the pyramid to the Language Representation
corner, Rojas-Garcia and Faber describe a semi-automatically extracted representation
of geographic terms from a text corpus, specifically describing rivers and bays, from which
they create semantic networks to explore underlying knowledge, thus moving towards the
Knowledge Representation corner. Addressing both the Language Representation and
Knowledge Representation corners, Doore, Sarrazin and Giudice present a place graph
model containing key, abstracted aspects of natural language descriptions in order to support
a user interface for navigation by blind and visually impaired museum visitors. Finally, at the
Knowledge Representation corner of the semantic pyramid, and the edges that connect it to
the Concepts and the Language Representation corners, Yokota and Khummongkol apply
6 Speaking of Location 2019
Mental Image Directed Semantic Theory to the problem of natural language understanding
in the robotics domain, linking machine and human language and conceptualisation. As can
be seen in Figure 3, the largest number of papers are at the Symbols corner of the pyramid,
addressing the nature of spatial and/or geospatial language, with few papers at the other
corners. While the study of spatial language is long standing, the incorporation of this
work into the multidisciplinary environment typified by the Speaking of Location workshop
series may reflect recognition of the need to consider the complexities of spatial language as
this field of research (addressing the automation of location description interpretation and
generation) matures. In particular we can regard this transdisciplinary approach as part
of a process of moving beyond what might be regarded as a superficial understanding to
the formulation and implementation of computable models of the way in which we describe
location using natural language.
5 Conclusions
The papers contained in these proceedings, and their presentation and discussion at the
Speaking of Location 2019 workshop provide a step towards the goal of realising the vision
of automated interpretation and generation of geospatial natural language, with all its
complexities, vagueness, under-specificity, context sensitivity and dynamism. The challenges
are still significant, and the research opportunities numerous, but the benefits of achieving
such a vision in the current text-rich environment indicate that this vision will continue to
be important going into the future.
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