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:
David Eick (né en 1968) est un producteur, mieux connu en tant que producteur de la série télévisée Battlestar Galactica (aux côtés de Ronald D. Moore), dont il a également écrit plusieurs épisodes, ainsi que de la version réinventée de Bionic Woman.
Postion	Tokenization
1	David
2	Eick
3	(
4	né
5	en
6	1968
7	)
8	est
9	un
10	producteur
11	,
12	mieux
13	connu
14	en
15	tant
16	que
17	producteur
18	de
19	la
20	série
21	télévisée
22	Battlestar
23	Galactica
24	(
25	aux
26	à
27	les
28	côtés
29	de
30	Ronald
31	D.
32	Moore
33	)
34	,
35	dont
36	il
37	a
38	également
39	écrit
40	plusieurs
41	épisodes
42	,
43	ainsi
44	que
45	de
46	la
47	version
48	réinventée
49	de
50	Bionic
51	Woman
52	.
Position	Tokenization	UPOS	Head	Deprel
1	David	PROPN	10	nsubj
2	Eick	PROPN	1	flat:name
3	(	PUNCT	4	punct
4	né	VERB	1	acl
5	en	ADP	6	case
6	1968	NUM	4	obl:arg
7	)	PUNCT	4	punct
8	est	AUX	10	cop
9	un	DET	10	det
10	producteur	NOUN	0	root
11	,	PUNCT	13	punct
12	mieux	ADV	13	advmod
13	connu	VERB	10	acl
14	en	ADP	17	case
15	tant	ADV	14	fixed
16	que	SCONJ	14	fixed
17	producteur	NOUN	13	obl:mod
18	de	ADP	20	case
19	la	DET	20	det
20	série	NOUN	17	nmod
21	télévisée	ADJ	20	amod
22	Battlestar	PROPN	20	appos
23	Galactica	PROPN	22	flat:name
24	(	PUNCT	25	punct
25	aux	_	None	_
26	à	ADP	20	advmod
27	les	DET	25	fixed
28	côtés	NOUN	25	fixed
29	de	ADP	29	case
30	Ronald	PROPN	25	obl:arg
31	D.	PROPN	29	flat:name
32	Moore	PROPN	30	flat:name
33	)	PUNCT	25	punct
34	,	PUNCT	25	punct
35	dont	PRON	40	nmod
36	il	PRON	38	nsubj
37	a	AUX	38	aux:tense
38	également	ADV	38	advmod
39	écrit	VERB	20	acl:relcl
40	plusieurs	DET	40	det
41	épisodes	NOUN	38	obj
42	,	PUNCT	46	punct
43	ainsi	ADV	46	cc
44	que	SCONJ	42	fixed
45	de	ADP	46	case
46	la	DET	46	det
47	version	NOUN	20	conj
48	réinventée	VERB	46	acl
49	de	ADP	49	case
50	Bionic	PROPN	46	nmod
51	Woman	PROPN	49	flat:name
52	.	PUNCT	10	punct