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 otro hallazgo del filme es la actriz Rona Hartner que, aparte de su impresionante ductilidad, aporta toda la frescura, vitalidad y picardía a su personaje.
Postion	Tokenization
1	El
2	otro
3	hallazgo
4	del
5	filme
6	es
7	la
8	actriz
9	Rona
10	Hartner
11	que
12	,
13	aparte
14	de
15	su
16	impresionante
17	ductilidad
18	,
19	aporta
20	toda
21	la
22	frescura
23	,
24	vitalidad
25	y
26	picardía
27	a
28	su
29	personaje
30	.
Position	Tokenization	UPOS	Head	Deprel
1	El	DET	3	det
2	otro	DET	1	det
3	hallazgo	NOUN	8	nsubj
4	del	ADP	5	case
5	filme	NOUN	3	nmod
6	es	AUX	8	cop
7	la	DET	8	det
8	actriz	NOUN	0	root
9	Rona	PROPN	8	appos
10	Hartner	PROPN	9	flat
11	que	PRON	19	nsubj
12	,	PUNCT	17	punct
13	aparte	ADV	17	case
14	de	ADP	13	fixed
15	su	DET	17	det
16	impresionante	ADJ	17	amod
17	ductilidad	NOUN	19	obl
18	,	PUNCT	17	punct
19	aporta	VERB	8	acl
20	toda	DET	21	det
21	la	DET	22	det
22	frescura	NOUN	19	obj
23	,	PUNCT	24	punct
24	vitalidad	NOUN	22	conj
25	y	CCONJ	26	cc
26	picardía	NOUN	22	conj
27	a	ADP	29	case
28	su	DET	29	det
29	personaje	NOUN	19	obj
30	.	PUNCT	8	punct