As a helpful and smart assistant, your task is to parse a given text in any language to Universal Dependency (UD) format including POS tags and dependency relations (HEAD and DEPREL).
Key Components of UD Annotation:
1. Tokens: The fundamental units within UD are tokens. These can be individual words, punctuation marks, or even parts of multi-word expressions. Each token has several associated attributes.
2. UPOS Tags: The UPOS field in the CoNLL-U format represents the universal part-of-speech tag assigned to each word. This tag is part of a universal POS tag set designed to be applicable across different languages. The UPOS tags include categories such as NOUN, VERB, ADJ (adjective), ADV (adverb), PRON (pronoun), DET (determiner), and more. 
3. Dependency Relations: Dependency relations are the core of the syntactic representation. They form a tree structure over the tokens in a sentence. Here's how they work:
    - HEAD: This field indicates the head of the current word. The head is the word that the current word is connected to in the dependency parse tree. The value is an integer that corresponds to the ID of the head word within the same sentence. A value of zero (0) indicates that the word is the root of the sentence.
    - DEPREL: The DEPREL field specifies the type of dependency relation between the current word and its head (as specified in the HEAD field). The value is a universal dependency relation or a language-specific subtype of such a relation.
Note: Blank lines are used to mark the boundaries between sentences.
Example:
Let's analyze this sentence with its UD annotation:
"The big dog chased the cat."
1. Tokenization:
- The
- big
- dog
- chased
- the
- cat
- .
2. UPOS Tags:
- The: DET
- big: ADJ
- dog: NOUN
- chased: VERB
- the: DET
- cat: NOUN
- .: PUNCT
3. Head node (parent):
- The: the parent of this word is "dog" at position 3
- big: the parent of this word is "dog" at position 3
- dog: the parent of this word is "chased" at position 4
- chased: this is the root node, therefore its head is 0
- the: the parent of this word is "cat" at position 6
- cat: the parent of this word is "chased" at position 4
- .: the parent of this word is "chased" at position 4
3. Dependency Relations:
- root(ROOT, chased)
- det(dog, The)
- amod(dog, big)
- nsubj(chased, dog)
- det(cat, the)
- obj(chased, cat)
Combining the above annotations, the final output in UD format is:
Position	Tokenization	UPOS	Head	Deprel
1	The	DET	3	det
2	big	ADJ	3	amod
3	dog	NOUN	4	nsubj
4	chased	VERB	0	ROOT
5	the	DET	6	det
6	cat	NOUN	4	obj
7	.	PUNCT	4	punct
Generate UD annotations for the following tokenized text:
L'Allemand Andreas Klöden auteur d'un meilleur contre-la-montre que l'Italien Ivan Basso devient le dauphin de Lance Armstrong à la veille de l'arrivée à Paris.
Postion	Tokenization
1	L'
2	Allemand
3	Andreas
4	Klöden
5	auteur
6	d'
7	un
8	meilleur
9	contre-la-montre
10	que
11	l'
12	Italien
13	Ivan
14	Basso
15	devient
16	le
17	dauphin
18	de
19	Lance
20	Armstrong
21	à
22	la
23	veille
24	de
25	l'
26	arrivée
27	à
28	Paris
29	.
Position	Tokenization	UPOS	Head	Deprel
1	L'	DET	2	det
2	Allemand	NOUN	15	nsubj
3	Andreas	PROPN	2	appos
4	Klöden	PROPN	3	flat:name
5	auteur	NOUN	2	appos
6	d'	ADP	9	case
7	un	DET	9	det
8	meilleur	ADJ	9	amod
9	contre-la-montre	NOUN	5	nmod
10	que	SCONJ	12	case
11	l'	DET	12	det
12	Italien	NOUN	8	obl:arg
13	Ivan	PROPN	12	appos
14	Basso	PROPN	13	flat:name
15	devient	VERB	0	root
16	le	DET	17	det
17	dauphin	NOUN	15	xcomp:pred
18	de	ADP	19	case
19	Lance	PROPN	17	nmod
20	Armstrong	PROPN	19	flat:name
21	à	ADP	23	case
22	la	DET	23	det
23	veille	NOUN	15	obl:mod
24	de	ADP	26	case
25	l'	DET	26	det
26	arrivée	NOUN	23	nmod
27	à	ADP	28	case
28	Paris	PROPN	26	nmod
29	.	PUNCT	15	punct