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 finlandés Mika Hakkinen fue el piloto más rápido en el primer día de los ensayos programados por ocho escuderías del Mundial en el Circuito de Jerez de la Frontera, al que volvió después de nueve años el español Pedro Martínez de la Rosa para rodar por primera vez en él con un Fórmula Uno.
Postion	Tokenization
1	El
2	finlandés
3	Mika
4	Hakkinen
5	fue
6	el
7	piloto
8	más
9	rápido
10	en
11	el
12	primer
13	día
14	de
15	los
16	ensayos
17	programados
18	por
19	ocho
20	escuderías
21	del
22	Mundial
23	en
24	el
25	Circuito
26	de
27	Jerez
28	de
29	la
30	Frontera
31	,
32	al
33	que
34	volvió
35	después
36	de
37	nueve
38	años
39	el
40	español
41	Pedro
42	Martínez
43	de
44	la
45	Rosa
46	para
47	rodar
48	por
49	primera
50	vez
51	en
52	él
53	con
54	un
55	Fórmula
56	Uno
57	.
Position	Tokenization	UPOS	Head	Deprel
1	El	DET	2	det
2	finlandés	NOUN	7	nsubj
3	Mika	PROPN	2	appos
4	Hakkinen	PROPN	3	flat
5	fue	AUX	7	cop
6	el	DET	7	det
7	piloto	NOUN	0	root
8	más	ADV	9	advmod
9	rápido	ADJ	7	amod
10	en	ADP	13	case
11	el	DET	13	det
12	primer	ADJ	13	amod
13	día	NOUN	7	obl
14	de	ADP	16	case
15	los	DET	16	det
16	ensayos	NOUN	13	nmod
17	programados	ADJ	16	amod
18	por	ADP	20	case
19	ocho	NUM	20	nummod
20	escuderías	NOUN	17	obj
21	del	ADP	22	case
22	Mundial	PROPN	20	nmod
23	en	ADP	25	case
24	el	DET	25	det
25	Circuito	PROPN	17	obl
26	de	ADP	27	case
27	Jerez	PROPN	25	flat
28	de	ADP	30	case
29	la	DET	30	det
30	Frontera	PROPN	25	flat
31	,	PUNCT	34	punct
32	al	ADP	33	case
33	que	PRON	34	obl
34	volvió	VERB	25	acl
35	después	ADV	34	advmod
36	de	ADP	38	case
37	nueve	NUM	38	nummod
38	años	NOUN	35	obl
39	el	DET	40	det
40	español	NOUN	34	nsubj
41	Pedro	PROPN	40	appos
42	Martínez	PROPN	41	flat
43	de	ADP	45	case
44	la	DET	45	det
45	Rosa	PROPN	41	flat
46	para	ADP	47	mark
47	rodar	VERB	34	advcl
48	por	ADP	50	case
49	primera	ADJ	50	amod
50	vez	NOUN	47	obl
51	en	ADP	52	case
52	él	PRON	47	obl
53	con	ADP	55	case
54	un	DET	55	det
55	Fórmula	PROPN	47	obl
56	Uno	PROPN	55	flat
57	.	PUNCT	7	punct