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<Paper uid="P06-2015">
  <Title>Sydney, July 2006. c(c)2006 Association for Computational Linguistics An Account for Compound Prepositions in Farsi</Title>
  <Section position="10" start_page="116" end_page="117" type="concl">
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2. N
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    <Paragraph position="0"> o should be morphologically simple and having all the features of [non-referential, abstract, complement-taking, indefinite]. Hereby it becomes clear why not every combination of &amp;quot;preposition + noun&amp;quot; lead to &amp;quot;compound prepositions&amp;quot; through incorporation, even if their occurrence bears a high frequency. The algorithm-like of this process is shown in figure 3.</Paragraph>
    <Paragraph position="1">  Figure 3 Prepositions are functional and so syntactic categories rather than lexical ones. I believe word formation of this category is motivated by syntax, in different ways one of which was argued here. This account contributes to the discipline of computational linguistics in labeling prepositions in Farsi, as this area of preposition labeling has been very challenging.</Paragraph>
    <Paragraph position="2"> Although Voutilainen (2003) believes that data-driven taggers seem to be better suited for the analysis of fixed-word-order poor-morphology languages like English, but the finding of this paper is applicable to Farsi parts of speech recognition at least in the area of compound prepositions.</Paragraph>
    <Paragraph position="3"> Prepositions are one sort of parts of speech, the recognition of which can be helpful in stemming for information retrieval (IR), since knowing a word's POS can help tell us which morphological affixes it can take. It can also help an IR application by helping select out nouns or other important words from a document.</Paragraph>
    <Paragraph position="4"> Automatic POS taggers can help in building automatic word-sense disambiguating algorithms, and POS taggers are also used in advanced ASR language models such as class-based n-grams (Jurafsky and Martin, 2000: 288)</Paragraph>
  </Section>
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