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 féretro de Vittorio Gassman fue recibido entre aplausos de miles de italianos que, dos horas antes de que se abrieran las puertas del Ayuntamiento de Roma, estaban ayer por la mañana en la calle para rendir homenaje al mítico actor fallecido el Jueves.
Postion	Tokenization
1	El
2	féretro
3	de
4	Vittorio
5	Gassman
6	fue
7	recibido
8	entre
9	aplausos
10	de
11	miles
12	de
13	italianos
14	que
15	,
16	dos
17	horas
18	antes
19	de
20	que
21	se
22	abrieran
23	las
24	puertas
25	del
26	Ayuntamiento
27	de
28	Roma
29	,
30	estaban
31	ayer
32	por
33	la
34	mañana
35	en
36	la
37	calle
38	para
39	rendir
40	homenaje
41	al
42	mítico
43	actor
44	fallecido
45	el
46	Jueves
47	.
Position	Tokenization	UPOS	Head	Deprel
1	El	DET	2	det
2	féretro	NOUN	7	nsubj
3	de	ADP	4	case
4	Vittorio	PROPN	2	nmod
5	Gassman	PROPN	4	flat
6	fue	AUX	7	aux
7	recibido	VERB	0	root
8	entre	ADP	9	case
9	aplausos	NOUN	7	obl
10	de	ADP	11	case
11	miles	NUM	9	nummod
12	de	ADP	13	case
13	italianos	NOUN	11	nmod
14	que	PRON	30	nsubj
15	,	PUNCT	18	punct
16	dos	NUM	17	nummod
17	horas	NOUN	18	obl
18	antes	ADV	30	advmod
19	de	ADP	22	mark
20	que	SCONJ	22	mark
21	se	PRON	22	expl:pass
22	abrieran	VERB	18	advcl
23	las	DET	24	det
24	puertas	NOUN	22	nsubj
25	del	ADP	26	case
26	Ayuntamiento	PROPN	24	nmod
27	de	ADP	28	case
28	Roma	PROPN	26	flat
29	,	PUNCT	18	punct
30	estaban	VERB	11	advcl
31	ayer	ADV	30	advmod
32	por	ADP	34	case
33	la	DET	34	det
34	mañana	NOUN	31	obl
35	en	ADP	37	case
36	la	DET	37	det
37	calle	NOUN	30	obl
38	para	ADP	39	mark
39	rendir	VERB	30	advcl
40	homenaje	NOUN	39	obj
41	al	ADP	43	case
42	mítico	ADJ	43	amod
43	actor	NOUN	39	obj
44	fallecido	ADJ	43	amod
45	el	DET	46	det
46	Jueves	NOUN	44	obl
47	.	PUNCT	7	punct