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revised lab 1 instructions

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## Chapter 1: explore the parallel UD treebank (PUD)
1. Go to https://universaldependencies.org/ and download Version 2.5 treebanks
1. Go to https://universaldependencies.org/ and download Version 2.7 treebanks
2. Look up the Parallel UD treebanks for those 19 languages that have it. They are named e.g. UD_English-PUD/
3. Select a language to compare with English.
4. Make statistics about the frequencies of POS tags and dependency labels in your language compared with English.
For instance, the top-10 tags/labels and their number of occurrences.
4. Make statistics about the frequencies of POS tags and dependency
labels in your language compared with English: find the top-20 tags/labels and their number of occurrences.
What does this tell you about the language?
5. Convert 2x2 tree from CoNLL format to graphical tree by hand, on paper.
Select a short English tree and its translation.
Then select a long English tree and its translation.
(This can be done with shell or Python programming or with the gf-ud tool.)
5. Convert the following four trees from CoNLL format to graphical
trees by hand, on paper.
- a short English tree (5-10 words, of your choice) and its translation.
- a long English tree (>25 words) and its translation.
6. Draw word alignments for some non-trivial example in the PUD treebank, on paper.
Use the same trees as in the previous question.
What can you say about the syntactic differences between the languages?
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## Chapter 3: UD syntax analysis
Take a bilingual corpus with English and your own language, and annotate with UD.
The English text is given in the file `comp-syntax-corpus-english.txt` in this directory.
The UD annotation that you produce manually can be simplified CoNLL, with just the fields
`position word postag head label`
@@ -48,10 +51,10 @@ expands to
`7 world _ NOUN _ _ 4 nmod _ _`
(Unfortunately, the tabs are not visible in the md output.)
The conversion to full CoNLL can be done using Python or `gf-ud reduced2conll`
Once you have full CoNLL, you can use for instance the gfud tool to visualize it.
The corpus is given in the file comp-syntax-corpus-english.txt in this directory.
Your task is to
1. write an English CoNLL file analysing this corpus
2. translate the corpus to your language