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:
Cristóbal Castro, padre de una alumna de Formación Profesional (FP) de Tarragona, denunció ayer la falta de previsión de Ensenyament por excluir por falta de plazas a la mitad de los alumnos que solicitaron un puesto en el nuevo curso puente de grado medio a grado superior en el instituto Vidal i Barraquer.
Postion	Tokenization
1	Cristóbal
2	Castro
3	,
4	padre
5	de
6	una
7	alumna
8	de
9	Formación
10	Profesional
11	(
12	FP
13	)
14	de
15	Tarragona
16	,
17	denunció
18	ayer
19	la
20	falta
21	de
22	previsión
23	de
24	Ensenyament
25	por
26	excluir
27	por
28	falta
29	de
30	plazas
31	a
32	la
33	mitad
34	de
35	los
36	alumnos
37	que
38	solicitaron
39	un
40	puesto
41	en
42	el
43	nuevo
44	curso
45	puente
46	de
47	grado
48	medio
49	a
50	grado
51	superior
52	en
53	el
54	instituto
55	Vidal
56	i
57	Barraquer
58	.
Position	Tokenization	UPOS	Head	Deprel
1	Cristóbal	PROPN	17	nsubj
2	Castro	PROPN	1	flat
3	,	PUNCT	4	punct
4	padre	NOUN	1	appos
5	de	ADP	7	case
6	una	DET	7	det
7	alumna	NOUN	4	nmod
8	de	ADP	9	case
9	Formación	PROPN	7	nmod
10	Profesional	PROPN	9	flat
11	(	PUNCT	12	punct
12	FP	PROPN	9	flat
13	)	PUNCT	12	punct
14	de	ADP	15	case
15	Tarragona	PROPN	9	nmod
16	,	PUNCT	4	punct
17	denunció	VERB	0	root
18	ayer	ADV	17	advmod
19	la	DET	20	det
20	falta	NOUN	17	obj
21	de	ADP	22	case
22	previsión	NOUN	20	nmod
23	de	ADP	24	case
24	Ensenyament	PROPN	22	nmod
25	por	ADP	26	mark
26	excluir	VERB	17	advcl
27	por	ADP	28	case
28	falta	NOUN	26	obl
29	de	ADP	30	case
30	plazas	NOUN	28	nmod
31	a	ADP	36	case
32	la	DET	31	fixed
33	mitad	NOUN	31	fixed
34	de	ADP	31	fixed
35	los	DET	36	det
36	alumnos	NOUN	26	obj
37	que	PRON	38	nsubj
38	solicitaron	VERB	36	acl
39	un	DET	40	det
40	puesto	NOUN	38	obj
41	en	ADP	44	case
42	el	DET	44	det
43	nuevo	ADJ	44	amod
44	curso	NOUN	38	obl
45	puente	NOUN	44	nmod
46	de	ADP	47	case
47	grado	NOUN	44	nmod
48	medio	ADJ	47	amod
49	a	ADP	50	case
50	grado	NOUN	47	nmod
51	superior	ADJ	50	amod
52	en	ADP	54	case
53	el	DET	54	det
54	instituto	NOUN	44	nmod
55	Vidal	PROPN	54	appos
56	i	CCONJ	57	cc
57	Barraquer	PROPN	55	conj
58	.	PUNCT	17	punct