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:
Milà aplaudió que el consistorio haya decidido estudiar nuevos equipamientos, así como habilitar el solar de la antigua fábrica Fytisa, en la calle de Sant Pau, como zona azul provisional para compensar la pérdida de plazas por la peatonalización del centro.
Postion	Tokenization
1	Milà
2	aplaudió
3	que
4	el
5	consistorio
6	haya
7	decidido
8	estudiar
9	nuevos
10	equipamientos
11	,
12	así
13	como
14	habilitar
15	el
16	solar
17	de
18	la
19	antigua
20	fábrica
21	Fytisa
22	,
23	en
24	la
25	calle
26	de
27	Sant
28	Pau
29	,
30	como
31	zona
32	azul
33	provisional
34	para
35	compensar
36	la
37	pérdida
38	de
39	plazas
40	por
41	la
42	peatonalización
43	del
44	centro
45	.
Position	Tokenization	UPOS	Head	Deprel
1	Milà	PROPN	2	nsubj
2	aplaudió	VERB	0	root
3	que	SCONJ	7	mark
4	el	DET	5	det
5	consistorio	NOUN	7	nsubj
6	haya	AUX	7	aux
7	decidido	VERB	2	ccomp
8	estudiar	VERB	7	xcomp
9	nuevos	ADJ	10	amod
10	equipamientos	NOUN	8	obj
11	,	PUNCT	14	punct
12	así	ADV	14	cc
13	como	SCONJ	12	fixed
14	habilitar	VERB	8	conj
15	el	DET	16	det
16	solar	NOUN	14	obj
17	de	ADP	20	case
18	la	DET	20	det
19	antigua	ADJ	20	amod
20	fábrica	NOUN	16	nmod
21	Fytisa	PROPN	20	appos
22	,	PUNCT	25	punct
23	en	ADP	25	case
24	la	DET	25	det
25	calle	NOUN	16	nmod
26	de	ADP	27	case
27	Sant	PROPN	25	nmod
28	Pau	PROPN	27	flat
29	,	PUNCT	25	punct
30	como	SCONJ	31	mark
31	zona	NOUN	14	obj
32	azul	ADJ	31	amod
33	provisional	ADJ	31	amod
34	para	ADP	35	mark
35	compensar	VERB	14	advcl
36	la	DET	37	det
37	pérdida	NOUN	35	obj
38	de	ADP	39	case
39	plazas	NOUN	37	nmod
40	por	ADP	42	case
41	la	DET	42	det
42	peatonalización	NOUN	37	nmod
43	del	ADP	44	case
44	centro	NOUN	42	nmod
45	.	PUNCT	2	punct