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:
El accidente que causó la muerte de una niña en el cruce de la calle de Aragó con el paseo de Gràcia, frente al antiguo Fashion Café, se ha saldado con una multa de 120.000 pesetas, un año de retirada del carnet y una indemnización de 19,7 millones de pesetas.
Postion	Tokenization
1	El
2	accidente
3	que
4	causó
5	la
6	muerte
7	de
8	una
9	niña
10	en
11	el
12	cruce
13	de
14	la
15	calle
16	de
17	Aragó
18	con
19	el
20	paseo
21	de
22	Gràcia
23	,
24	frente
25	al
26	antiguo
27	Fashion
28	Café
29	,
30	se
31	ha
32	saldado
33	con
34	una
35	multa
36	de
37	120.000
38	pesetas
39	,
40	un
41	año
42	de
43	retirada
44	del
45	carnet
46	y
47	una
48	indemnización
49	de
50	19,7
51	millones
52	de
53	pesetas
54	.
Position	Tokenization	UPOS	Head	Deprel
1	El	DET	2	det
2	accidente	NOUN	32	nsubj
3	que	PRON	4	nsubj
4	causó	VERB	2	acl
5	la	DET	6	det
6	muerte	NOUN	4	obj
7	de	ADP	9	case
8	una	DET	9	det
9	niña	NOUN	6	nmod
10	en	ADP	12	case
11	el	DET	12	det
12	cruce	NOUN	4	obl
13	de	ADP	15	case
14	la	DET	15	det
15	calle	NOUN	12	nmod
16	de	ADP	17	case
17	Aragó	PROPN	15	nmod
18	con	ADP	20	case
19	el	DET	20	det
20	paseo	NOUN	12	nmod
21	de	ADP	22	case
22	Gràcia	PROPN	20	nmod
23	,	PUNCT	27	punct
24	frente	NOUN	27	case
25	al	ADP	24	fixed
26	antiguo	ADJ	27	amod
27	Fashion	PROPN	12	nmod
28	Café	PROPN	27	flat
29	,	PUNCT	27	punct
30	se	PRON	32	expl:pass
31	ha	AUX	32	aux
32	saldado	VERB	0	root
33	con	ADP	35	case
34	una	DET	35	det
35	multa	NOUN	32	obl
36	de	ADP	38	case
37	120.000	NUM	38	nummod
38	pesetas	NOUN	35	nmod
39	,	PUNCT	41	punct
40	un	DET	41	det
41	año	NOUN	35	appos
42	de	ADP	43	case
43	retirada	NOUN	41	nmod
44	del	ADP	45	case
45	carnet	NOUN	43	nmod
46	y	CCONJ	48	cc
47	una	DET	48	det
48	indemnización	NOUN	35	conj
49	de	ADP	51	case
50	19,7	NUM	51	nummod
51	millones	NOUN	48	nmod
52	de	ADP	53	case
53	pesetas	NOUN	51	nmod
54	.	PUNCT	32	punct