Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Geographic Question Answering: Challenges, Uniqueness, Classification,
  and Future Directions   As an important part of Artificial Intelligence (AI), Question Answering (QA)
aims at generating answers to questions phrased in natural language. While
there has been substantial progress in open-domain question answering, QA
systems are still struggling to answer questions which involve geographic
entities or concepts and that require spatial operations. In this paper, we
discuss the problem of geographic question answering (GeoQA). We first
investigate the reasons why geographic questions are difficult to answer by
analyzing challenges of geographic questions. We discuss the uniqueness of
geographic questions compared to general QA. Then we review existing work on
GeoQA and classify them by the types of questions they can address. Based on
this survey, we provide a generic classification framework for geographic
questions. Finally, we conclude our work by pointing out unique future research
directions for GeoQA.

17
The categories of this paper are: q-fin
15
The categories of this paper are: nucl-ex
21
The categories of this paper are: adap-org
31
The categories of this paper are: ao-sci
25
The categories of this paper are: patt-sol
26
The categories of this paper are: bayes-an
35
The categories of this paper are: mtrl-th
13
The categories of this paper are: quant-ph
6
The categories of this paper are: astro-ph
28
The categories of this paper are: alg-geom
36
The categories of this paper are: cmp-lg
2
The categories of this paper are: math
23
The categories of this paper are: solv-int
11
The categories of this paper are: hep-lat
12
The categories of this paper are: nucl-th
24
The categories of this paper are: dg-ga