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:
Lara Fabian, Roch Voisine, Marie-Elaine Thibert, Ima, Bruno Pelletier, Francesca Gagnon, Dan Bigras, Judith Bérard, Patrick Fiori, Chimène Badi, Marie-Pier Perreault, Suzie Villeneuve et plusieurs d'autres ont fait appel aux talents d'auteur compositeur de Thoma.
Postion	Tokenization
1	Lara
2	Fabian
3	,
4	Roch
5	Voisine
6	,
7	Marie-Elaine
8	Thibert
9	,
10	Ima
11	,
12	Bruno
13	Pelletier
14	,
15	Francesca
16	Gagnon
17	,
18	Dan
19	Bigras
20	,
21	Judith
22	Bérard
23	,
24	Patrick
25	Fiori
26	,
27	Chimène
28	Badi
29	,
30	Marie-Pier
31	Perreault
32	,
33	Suzie
34	Villeneuve
35	et
36	plusieurs
37	d'
38	autres
39	ont
40	fait
41	appel
42	aux
43	à
44	les
45	talents
46	d'
47	auteur
48	compositeur
49	de
50	Thoma
51	.
Position	Tokenization	UPOS	Head	Deprel
1	Lara	PROPN	40	nsubj
2	Fabian	PROPN	1	flat:name
3	,	PUNCT	4	punct
4	Roch	PROPN	1	conj
5	Voisine	PROPN	4	flat:name
6	,	PUNCT	7	punct
7	Marie-Elaine	PROPN	1	conj
8	Thibert	PROPN	7	flat:name
9	,	PUNCT	10	punct
10	Ima	PROPN	1	conj
11	,	PUNCT	12	punct
12	Bruno	PROPN	1	conj
13	Pelletier	PROPN	12	flat:name
14	,	PUNCT	15	punct
15	Francesca	PROPN	1	conj
16	Gagnon	PROPN	15	flat:name
17	,	PUNCT	18	punct
18	Dan	PROPN	1	conj
19	Bigras	PROPN	18	flat:name
20	,	PUNCT	21	punct
21	Judith	PROPN	1	conj
22	Bérard	PROPN	21	flat:name
23	,	PUNCT	24	punct
24	Patrick	PROPN	1	conj
25	Fiori	PROPN	24	flat:name
26	,	PUNCT	27	punct
27	Chimène	PROPN	1	conj
28	Badi	PROPN	27	flat:name
29	,	PUNCT	30	punct
30	Marie-Pier	PROPN	1	conj
31	Perreault	PROPN	30	flat:name
32	,	PUNCT	33	punct
33	Suzie	PROPN	1	conj
34	Villeneuve	PROPN	33	flat:name
35	et	CCONJ	36	cc
36	plusieurs	PRON	1	conj
37	d'	ADP	38	case
38	autres	PRON	36	nmod
39	ont	AUX	40	aux:tense
40	fait	VERB	0	root
41	appel	NOUN	40	obj:lvc
42	aux	_	None	_
43	à	ADP	44	case
44	les	DET	44	det
45	talents	NOUN	41	dep:comp
46	d'	ADP	46	case
47	auteur	NOUN	44	nmod
48	compositeur	NOUN	46	nmod
49	de	ADP	49	case
50	Thoma	PROPN	44	nmod
51	.	PUNCT	40	punct