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:
Les futurs cas d'Alzheimer peuvent être prédits avec plusieurs années d'avance avec près de 100% d'exactitude grâce à des marqueurs biologiques présents dans le liquide céphalo-rachidien.
Postion	Tokenization
1	Les
2	futurs
3	cas
4	d'
5	Alzheimer
6	peuvent
7	être
8	prédits
9	avec
10	plusieurs
11	années
12	d'
13	avance
14	avec
15	près
16	de
17	100
18	%
19	d'
20	exactitude
21	grâce
22	à
23	des
24	marqueurs
25	biologiques
26	présents
27	dans
28	le
29	liquide
30	céphalo-rachidien
31	.
Position	Tokenization	UPOS	Head	Deprel
1	Les	DET	3	det
2	futurs	ADJ	3	amod
3	cas	NOUN	6	nsubj
4	d'	ADP	5	case
5	Alzheimer	PROPN	3	nmod
6	peuvent	VERB	0	root
7	être	AUX	8	aux:pass
8	prédits	VERB	6	xcomp:obj
9	avec	ADP	11	case
10	plusieurs	DET	11	det
11	années	NOUN	8	obl:mod
12	d'	ADP	13	case
13	avance	NOUN	11	nmod
14	avec	ADP	15	case
15	près	ADV	11	nmod
16	de	ADP	18	case
17	100	NUM	18	nummod
18	%	SYM	15	dep:comp
19	d'	ADP	20	case
20	exactitude	NOUN	18	nmod
21	grâce	NOUN	24	case
22	à	ADP	21	fixed
23	des	DET	24	det
24	marqueurs	NOUN	8	obl:mod
25	biologiques	ADJ	24	amod
26	présents	ADJ	24	amod
27	dans	ADP	29	case
28	le	DET	29	det
29	liquide	NOUN	26	obl:mod
30	céphalo-rachidien	ADJ	29	amod
31	.	PUNCT	6	punct