You will be presented with a citation segment from the section of an NLP research paper, as well as the context surrounding that citation. Classify the intent behind this citation by choosing from one of the following categories:
- Background: provides context or foundational information related to the topic.
- Extends: builds upon the cited work.
- Uses: applies the methods or findings of the cited work.
- Motivation: cites the work as inspiration or rationale for the research.
- CompareOrContrast: compares or contrasts the cited work with others.
- FutureWork: cites the work as a direction for future research.

Your answer should be a single word from the following list of options: ["Background", "Extends", "Uses", "Motivation", "CompareOrContrast", "FutureWork"]. Do not include any other text in your response.

Section Title:
introduction

Context before the citation:
More specifically, the notion of the phrasal lexicon (used first by Becker 1975) has been used successfully in a number of areas:  Accordingly, they generate lexical correspondences by means of co-occurrence measures and string similarity metrics. Ahrenberg, Andersson, and Merkel (2002) observe that for less widely spoken languages, the relative lack of linguistic tools and resources has forced developers of word alignment tools for such languages to use shallow processing and basic statistical approaches to word linking.

Citation Sentence:
More specifically , the notion of the phrasal lexicon ( used first by Becker 1975 ) has been used successfully in a number of areas :

Context after the citation:
â¢ Learnability (Zernik and Dyer 1987) â¢ Text generation (Hovy 1988; Milosavljevic, Tulloch, and Dale 1996) â¢ Speech generation (Rayner and Carter 1997) â¢ Localization (SchÂ¨aler 1996)  More recently, Simard and Langlais (2001) have proposed the exploitation of TMs at a subsentential level, while Carl, Way, and SchÂ¨aler (2002) and SchÂ¨aler, Way, and Carl (2003, pages 108â109) describe how phrasal lexicons might come to occupy a central place in a future hybrid integrated translation environment. This, they suggest, may result in a paradigm shift from TM to EBMT via the phrasal lexicon: Translators are on the whole wary of MT technology, but once subsentential alignment is enabled, translators will become aware of the benefits to be gained from (source, target) phrasal segments, and from there they suggest that âit is a reasonably short step to enabling an automated solution via the recombination element of EBMT systems such as those described in [Carl and Way 2003].â In this section, we describe how the memory of our EBMT system is seeded with a set of translations obtained from Web-based MT systems.
Background