Your task is to classify the citation intent within the following provided text from a computational linguistics research paper. The cited work is demarcated by "<cite>" and "</cite>". Determine the purpose of the cited work by selecting from the listed categories:

- Background: The cited paper underpins the subject matter.
- Motivation: The cited paper inspires or provides a rationale for the current research.
- Uses: The current work utilizes concepts or tools from the cited paper.
- Extends: The current work advances ideas or methods from the cited paper.
- Similarities: The current work identifies commonalities with the cited paper.
- Differences: The current work delineates its distinction from the cited paper.
- FutureWork: The cited paper is acknowledged as groundwork for prospective research.

Indicate the intents by listing them in a `json` array, e.g. ["Background", "Uses"]. More than one intent may be applicable. Do not include any extraneous text in your response.

Context with Citation:
It is a popular tool in semantic parsing, and treebank creation efforts have been made for Turkish (Ç akıcı, 2005) , German (Hockenmaier, 2006) , English <cite>(Hockenmaier and Steedman, 2007)</cite> , Italian (Bos et al., 2009) , Chinese (Tse and Curran, 2010) , Arabic (Boxwell and Brew, 2010) , Japanese (Uematsu et al., 2013) , and Hindi (Ambati et al., 2018) . However, all of these treebanks were not directly annotated according to the CCG formalism, but automatically converted from phrase structure or dependency treebanks, which is an error-prone process. Direct annotation in CCG has so far mostly been limited to small datasets for seeding or testing semantic parsers (e.g., Artzi et al., 2015) , and no graphical annotation interface is available to support such efforts, making the annotation process difficult to scale. The only exceptions we are aware of are the Groningen Meaning Bank and the Parallel Meaning Bank (Abzianidze et al., 2017) , two annotation efforts which use a graphical user interface for annotating sentences with CCG derivations and other annotation layers, and which have produced CCG treebanks for English, German, Italian, and Dutch. However, these efforts are focused on semantics and have not released explicit guidelines for syntactic annotation. Their annotation tool is limited in that annotators only have control over lexical categories, not larger constituents. Even though CCG is a lexicalized formalism, where most decisions can be made on the lexical level, there is no full control over attachment phenomena in the lexicon. Moreover, these annotation tools are not open-source and cannot easily be deployed to support other annotation efforts. In this paper, we present an open-source, lightweight, easy-to-use graphical annotation tool that employs a statistical parser to create initial CCG derivations for sentences, and allows annotators to correct these annotations via lexical category constraints and span constraints.
["Motivation"]