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:
Hakkinen completó treinta vueltas al circuito jerezano y el que más se acercó a su mejor tiempo fue el italiano Jarno Trulli (Jordan), que, tras 41 giros, fue el segundo más rápido con 1:25.67.
Postion	Tokenization
1	Hakkinen
2	completó
3	treinta
4	vueltas
5	al
6	circuito
7	jerezano
8	y
9	el
10	que
11	más
12	se
13	acercó
14	a
15	su
16	mejor
17	tiempo
18	fue
19	el
20	italiano
21	Jarno
22	Trulli
23	(
24	Jordan
25	)
26	,
27	que
28	,
29	tras
30	41
31	giros
32	,
33	fue
34	el
35	segundo
36	más
37	rápido
38	con
39	1:25.67
40	.
Position	Tokenization	UPOS	Head	Deprel
1	Hakkinen	PROPN	2	nsubj
2	completó	VERB	0	root
3	treinta	NUM	4	nummod
4	vueltas	NOUN	2	obj
5	al	ADP	6	case
6	circuito	NOUN	4	nmod
7	jerezano	ADJ	6	amod
8	y	CCONJ	20	cc
9	el	DET	13	det
10	que	PRON	13	nsubj
11	más	ADV	13	advmod
12	se	PRON	13	expl:pv
13	acercó	VERB	20	csubj
14	a	ADP	17	case
15	su	DET	17	det
16	mejor	ADJ	17	amod
17	tiempo	NOUN	13	obl
18	fue	AUX	20	cop
19	el	DET	20	det
20	italiano	NOUN	2	conj
21	Jarno	PROPN	20	appos
22	Trulli	PROPN	21	flat
23	(	PUNCT	24	punct
24	Jordan	PROPN	20	appos
25	)	PUNCT	24	punct
26	,	PUNCT	35	punct
27	que	PRON	35	nsubj
28	,	PUNCT	31	punct
29	tras	ADP	31	case
30	41	NUM	31	nummod
31	giros	NOUN	35	obl
32	,	PUNCT	31	punct
33	fue	AUX	35	cop
34	el	DET	35	det
35	segundo	ADJ	20	acl
36	más	ADV	37	advmod
37	rápido	ADJ	35	amod
38	con	ADP	39	case
39	1:25.67	NUM	35	obl
40	.	PUNCT	2	punct