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:
En las tres últimas temporadas el fino y disciplinado equipo de la Universidad de Duke ha sido la pesadilla y el desmitificador absoluto de los - Fab Five -, los cinco superjugadores reclutados simultáneamente hace dos años y medio por Steve Fisher, el entrenador de la Universidad de Michigan.
Postion	Tokenization
1	En
2	las
3	tres
4	últimas
5	temporadas
6	el
7	fino
8	y
9	disciplinado
10	equipo
11	de
12	la
13	Universidad
14	de
15	Duke
16	ha
17	sido
18	la
19	pesadilla
20	y
21	el
22	desmitificador
23	absoluto
24	de
25	los
26	-
27	Fab
28	Five
29	-
30	,
31	los
32	cinco
33	superjugadores
34	reclutados
35	simultáneamente
36	hace
37	dos
38	años
39	y
40	medio
41	por
42	Steve
43	Fisher
44	,
45	el
46	entrenador
47	de
48	la
49	Universidad
50	de
51	Michigan
52	.
Position	Tokenization	UPOS	Head	Deprel
1	En	ADP	5	case
2	las	DET	5	det
3	tres	NUM	2	nummod
4	últimas	ADJ	5	amod
5	temporadas	NOUN	19	obl
6	el	DET	10	det
7	fino	ADJ	10	amod
8	y	CCONJ	9	cc
9	disciplinado	ADJ	7	conj
10	equipo	NOUN	19	nsubj
11	de	ADP	13	case
12	la	DET	13	det
13	Universidad	PROPN	10	nmod
14	de	ADP	15	case
15	Duke	PROPN	13	flat
16	ha	AUX	19	aux
17	sido	AUX	19	cop
18	la	DET	19	det
19	pesadilla	NOUN	0	root
20	y	CCONJ	22	cc
21	el	DET	22	det
22	desmitificador	NOUN	19	conj
23	absoluto	ADJ	22	amod
24	de	ADP	27	case
25	los	DET	27	det
26	-	PUNCT	27	punct
27	Fab	PROPN	19	nmod
28	Five	PROPN	27	flat
29	-	PUNCT	27	punct
30	,	PUNCT	33	punct
31	los	DET	33	det
32	cinco	NUM	31	nummod
33	superjugadores	NOUN	27	appos
34	reclutados	ADJ	33	amod
35	simultáneamente	ADV	34	advmod
36	hace	VERB	34	advcl
37	dos	NUM	38	nummod
38	años	NOUN	36	obj
39	y	CCONJ	40	cc
40	medio	NUM	38	conj
41	por	ADP	42	case
42	Steve	PROPN	34	obj
43	Fisher	PROPN	42	flat
44	,	PUNCT	46	punct
45	el	DET	46	det
46	entrenador	NOUN	42	appos
47	de	ADP	49	case
48	la	DET	49	det
49	Universidad	PROPN	46	nmod
50	de	ADP	51	case
51	Michigan	PROPN	49	flat
52	.	PUNCT	19	punct