=Paper=
{{Paper
|id=Vol-1660/ecs-paper5
|storemode=property
|title=Categorizing Questions Through the Demonstrative-Intentional Tree
|pdfUrl=https://ceur-ws.org/Vol-1660/ecs-paper5.pdf
|volume=Vol-1660
|authors=Sezen Altuǧ
|dblpUrl=https://dblp.org/rec/conf/fois/Altug16
}}
==Categorizing Questions Through the Demonstrative-Intentional Tree==
https://ceur-ws.org/Vol-1660/ecs-paper5.pdf
Categorizing Questions Through the
Demonstrative-Intentional Tree
Sezen ALTUĞ
Laboratory for Computational Ontology,
Middle East Technical University, Ankara
1. Introduction
Our project aims at providing a philosophical analysis of questions. It surveys
question-types for investigating whether questions can be categorized based on
their identical and distinctive characters with/from each other. It can also be ac-
knowledged as a first step towards an ontology of questions, although implement-
ing a computational ontology is not among our current concerns. This project
has the potential for explaining the intrinsic structures of dynamics of science [1]:
because of their interrogative form, questions are the fundamentals of scientific
inquiries and their investigation could therefore clarify how science works, how
scientists explore and benefit the various methods used for different research pro-
grams. Our effort can be located at the computational level of Marr’s Tri-Level
Hypothesis [2], and will be contrasted with alternative strategies.
2. Literature
For this study, we have mostly consulted the philosophical or descriptive papers
dealing with interrogative quality of questions [1,3,4,5], their formal classifica-
tions, alternative logical systems employing questions as premises and conclusions
in arguments [6,7,8], and have worked through glossaries of logical and linguistic
terms, and different disciplines of social sciences.
3. Methodology
Within the study, questions are analyzed according to whether they include
question-words or any other interrogative phrase, the complexity of the sen-
tence structures such as including connectives, the prevalence of reference to
the required information over different scientific domains, etc. We devised
on this basis ten conceptual trees for categorizing questions: Question-Type
Tree, Question-Domain Tree, Universal-Particular Tree, Qualitative-Quantitative
Tree, Demonstrative-Intentional Tree, Structural-Functional-Organizational Tree,
Modality Tree, Operator Bounded Tree, Problem-Model Based Tree, and Agen-
tive Tree.
One of the conceptual trees built for categorizing questions is based on the
distinction between demonstrative and intentional questions. The main classifica-
tion principle of this tree is to consider whether questions seek for an explanation
or a description or imply a specific intention. Accordingly, the tree encompasses
the two main categories demonstrative and intentional. The questions falling un-
der the category demonstrative ask for a description or explanation such as “Why
does supernova threaten our world?”. This category further divides into the two
subcategories: descriptive and explanatory. The latter consists of questions sup-
ported by a specific method of inference to find the required information, either
inductively, deductively or abductively, e.g., “Does smoking increase the risk of
cancer?”, “Why did the apple fall on Newtons head?”, and “To what extent, is
the reason of increase in car accidents a rainy season?”. The former is composed of
the categories commentary (“Do you think that Kuhn was right in his criticism to
Popper about how science proceeds?”) and definitional. The nature of the latter
varies with respect to whether they ask for attributions (“What was the expected
structure of Mars’ surface before the probes sent to gather samples?”), properties
(“What will be the size of a meteorite that can give an irreversible damage to the
life on Earth?”), and relations (“Are there any differences between a plant based
and vegan diet?”).
The other second main category of the tree is intentionality. It encompasses
questions which have a sort of directedness towards an entity or refer to a specific
content, for instance, “Why does John take cooking classes?”. This category has
two other subcategories: purposiveness and novelty-based. While the subcategory
purposiveness consists of questions which ask the intention of the agent as plans
respecting daily routine, professions or any other domain (“Why do couples prefer
to spend their honeymoon in exotic places?”), the subcategory novelty-based looks
for the intention of the agent when doing something innovative. The latter is also
divided between discovery-leading (“What is the evidence for the existence of
liquid water on Mars?”) and inventional (“What are the requirements for building
an operating system for the Internet of Things?”).
References
[1] J. Hintikka. Inquiry as Inquiry: A Logic of Scientific Discovery. Jaakko Hintikka Selected
Papers. Springer Netherlands, 1999.
[2] D. Marr and T. Poggio. From understanding computation to understanding neural circuitry.
Technical report, Massachusetts Institute of Technology, Cambridge, MA, USA, 1976.
[3] I. Clardelli, J. Groenendijk, and F. Roelofsen. Inquisitive semantics: a new notion of mean-
ing. Language and Linguistics Compass, 7:459–476, 2013.
[4] H. Hiz. Introduction. In H. Hiz, editor, Questions, pages IX–XVII. Reidel Publishing
Company, Dordrecht, Holland / Boston, U.S.A., 1978.
[5] D. Walton. The fallacy of many questions: On the notations of complexity, loadedness and
unfair entrapment in interrogative theory. Argumentation, 13:379–383, 1999.
[6] R. G. Collingwood. An autobiography. USA: Oxford University Press, 1939.
[7] A. Prior and M. Prior. Erotetic logic. The Philosophical Review, 64:43–59, 1955.
[8] A. Wiśniewski. Questions, Inferences, and Scenarios, volume 46 of Studies in Logic. College
Publications, 2013.