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:
Las multas más elevadas han sido impuestas a las compañías Ras (grupo Allianz), Sai (Ligresti), Generali, Assitalia, Lloyd Adriático y Winterthur, que deberán pagar al erario público 9.400 millones de pesetas, 7.030, 5.910, 5.290, 5.008 y 4.120, respectivamente.
Postion	Tokenization
1	Las
2	multas
3	más
4	elevadas
5	han
6	sido
7	impuestas
8	a
9	las
10	compañías
11	Ras
12	(
13	grupo
14	Allianz
15	)
16	,
17	Sai
18	(
19	Ligresti
20	)
21	,
22	Generali
23	,
24	Assitalia
25	,
26	Lloyd
27	Adriático
28	y
29	Winterthur
30	,
31	que
32	deberán
33	pagar
34	al
35	erario
36	público
37	9.400
38	millones
39	de
40	pesetas
41	,
42	7.030
43	,
44	5.910
45	,
46	5.290
47	,
48	5.008
49	y
50	4.120
51	,
52	respectivamente
53	.
Position	Tokenization	UPOS	Head	Deprel
1	Las	DET	2	det
2	multas	NOUN	7	nsubj
3	más	ADV	4	advmod
4	elevadas	ADJ	2	amod
5	han	AUX	7	aux
6	sido	AUX	7	aux
7	impuestas	VERB	0	root
8	a	ADP	10	case
9	las	DET	10	det
10	compañías	NOUN	7	obj
11	Ras	PROPN	10	appos
12	(	PUNCT	13	punct
13	grupo	NOUN	11	appos
14	Allianz	PROPN	13	appos
15	)	PUNCT	13	punct
16	,	PUNCT	17	punct
17	Sai	PROPN	11	conj
18	(	PUNCT	19	punct
19	Ligresti	PROPN	17	flat
20	)	PUNCT	19	punct
21	,	PUNCT	22	punct
22	Generali	PROPN	11	conj
23	,	PUNCT	24	punct
24	Assitalia	PROPN	11	conj
25	,	PUNCT	26	punct
26	Lloyd	PROPN	11	conj
27	Adriático	PROPN	26	flat
28	y	CCONJ	29	cc
29	Winterthur	PROPN	11	conj
30	,	PUNCT	33	punct
31	que	PRON	33	nsubj
32	deberán	AUX	33	aux
33	pagar	VERB	10	acl
34	al	ADP	35	case
35	erario	NOUN	33	obj
36	público	ADJ	35	amod
37	9.400	NUM	38	nummod
38	millones	NOUN	33	obj
39	de	ADP	40	case
40	pesetas	NOUN	38	nmod
41	,	PUNCT	42	punct
42	7.030	NUM	38	appos
43	,	PUNCT	44	punct
44	5.910	NUM	38	appos
45	,	PUNCT	46	punct
46	5.290	NUM	38	appos
47	,	PUNCT	48	punct
48	5.008	NUM	38	appos
49	y	CCONJ	50	cc
50	4.120	NUM	38	conj
51	,	PUNCT	52	punct
52	respectivamente	ADV	38	advmod
53	.	PUNCT	7	punct