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:
À mille lieues des films à effets spéciaux dont il est le maître, Steven Spielberg renoue avec une vraie esthétique picturale, aussi simple que travaillée.
Postion	Tokenization
1	À
2	mille
3	lieues
4	des
5	de
6	les
7	films
8	à
9	effets
10	spéciaux
11	dont
12	il
13	est
14	le
15	maître
16	,
17	Steven
18	Spielberg
19	renoue
20	avec
21	une
22	vraie
23	esthétique
24	picturale
25	,
26	aussi
27	simple
28	que
29	travaillée
30	.
Position	Tokenization	UPOS	Head	Deprel
1	À	ADP	3	case
2	mille	NUM	3	nummod
3	lieues	NOUN	18	obl:mod
4	des	_	None	_
5	de	ADP	6	case
6	les	DET	6	det
7	films	NOUN	3	nmod
8	à	ADP	8	case
9	effets	NOUN	6	nmod
10	spéciaux	ADJ	8	amod
11	dont	PRON	14	nmod
12	il	PRON	14	nsubj
13	est	AUX	14	cop
14	le	DET	14	det
15	maître	NOUN	6	acl:relcl
16	,	PUNCT	3	punct
17	Steven	PROPN	18	nsubj
18	Spielberg	PROPN	16	flat:name
19	renoue	VERB	0	root
20	avec	ADP	22	case
21	une	DET	22	det
22	vraie	ADJ	22	amod
23	esthétique	NOUN	18	obl:arg
24	picturale	ADJ	22	amod
25	,	PUNCT	26	punct
26	aussi	ADV	26	advmod
27	simple	ADJ	22	amod
28	que	SCONJ	28	mark
29	travaillée	VERB	25	ccomp:obj
30	.	PUNCT	18	punct