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:
Après son succès aux 24 Heures du Mans et ses nombreuses victoires en compétition, l'Audi R15 TDI Plus fait à nouveau triompher la technologie de la firme d'Ingolstadt.
Postion	Tokenization
1	Après
2	son
3	succès
4	aux
5	à
6	les
7	24
8	Heures
9	du
10	de
11	le
12	Mans
13	et
14	ses
15	nombreuses
16	victoires
17	en
18	compétition
19	,
20	l'
21	Audi
22	R15
23	TDI
24	Plus
25	fait
26	à
27	nouveau
28	triompher
29	la
30	technologie
31	de
32	la
33	firme
34	d'
35	Ingolstadt
36	.
Position	Tokenization	UPOS	Head	Deprel
1	Après	ADP	3	case
2	son	DET	3	det
3	succès	NOUN	26	obl:mod
4	aux	_	None	_
5	à	ADP	7	case
6	les	DET	7	det
7	24	NUM	7	nummod
8	Heures	NOUN	3	nmod
9	du	_	None	_
10	de	ADP	10	case
11	le	DET	10	det
12	Mans	PROPN	7	nmod
13	et	CCONJ	14	cc
14	ses	DET	14	det
15	nombreuses	ADJ	14	amod
16	victoires	NOUN	3	conj
17	en	ADP	16	case
18	compétition	NOUN	14	nmod
19	,	PUNCT	3	punct
20	l'	DET	19	det
21	Audi	PROPN	26	nsubj:caus
22	R15	X	19	flat:name
23	TDI	X	20	flat:name
24	Plus	ADV	21	flat:name
25	fait	AUX	26	aux:caus
26	à	ADP	26	advmod
27	nouveau	ADJ	24	fixed
28	triompher	VERB	0	root
29	la	DET	28	det
30	technologie	NOUN	26	obj:agent
31	de	ADP	31	case
32	la	DET	31	det
33	firme	NOUN	28	nmod
34	d'	ADP	33	case
35	Ingolstadt	PROPN	31	nmod
36	.	PUNCT	26	punct