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:
Uno de sus personajes más populares fue el Sargento Arensibia de Historias de la puta mili, un montaje teatral que vieron más de un millón de espectadores en toda España y del que posteriormente se grabó una serie de televisión.
Postion	Tokenization
1	Uno
2	de
3	sus
4	personajes
5	más
6	populares
7	fue
8	el
9	Sargento
10	Arensibia
11	de
12	Historias
13	de
14	la
15	puta
16	mili
17	,
18	un
19	montaje
20	teatral
21	que
22	vieron
23	más
24	de
25	un
26	millón
27	de
28	espectadores
29	en
30	toda
31	España
32	y
33	del
34	que
35	posteriormente
36	se
37	grabó
38	una
39	serie
40	de
41	televisión
42	.
Position	Tokenization	UPOS	Head	Deprel
1	Uno	PRON	9	nsubj
2	de	ADP	4	case
3	sus	DET	4	det
4	personajes	NOUN	1	nmod
5	más	ADV	6	advmod
6	populares	ADJ	4	amod
7	fue	AUX	9	cop
8	el	DET	9	det
9	Sargento	PROPN	0	root
10	Arensibia	PROPN	9	flat
11	de	ADP	12	case
12	Historias	PROPN	9	nmod
13	de	ADP	15	case
14	la	DET	15	det
15	puta	PROPN	12	flat
16	mili	PROPN	15	flat
17	,	PUNCT	19	punct
18	un	DET	19	det
19	montaje	NOUN	12	appos
20	teatral	ADJ	19	amod
21	que	PRON	22	obj
22	vieron	VERB	19	acl
23	más	ADV	26	advmod
24	de	ADP	26	case
25	un	NUM	26	nummod
26	millón	NOUN	28	nmod
27	de	ADP	26	case
28	espectadores	NOUN	22	nsubj
29	en	ADP	31	case
30	toda	DET	31	det
31	España	PROPN	22	obl
32	y	CCONJ	37	cc
33	del	ADP	34	case
34	que	PRON	37	obl
35	posteriormente	ADV	37	advmod
36	se	PRON	37	expl:pass
37	grabó	VERB	22	conj
38	una	DET	39	det
39	serie	NOUN	37	nsubj
40	de	ADP	41	case
41	televisión	NOUN	39	nmod
42	.	PUNCT	9	punct