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:
"Nos hizo mucha ilusión que Barbie no sólo haya servido de diversión a las niñas, sino que pueda ayudar a los adultos que hayan sufrido un accidente", indicó un portavoz de la casa Mattel.
Postion	Tokenization
1	"
2	Nos
3	hizo
4	mucha
5	ilusión
6	que
7	Barbie
8	no
9	sólo
10	haya
11	servido
12	de
13	diversión
14	a
15	las
16	niñas
17	,
18	sino
19	que
20	pueda
21	ayudar
22	a
23	los
24	adultos
25	que
26	hayan
27	sufrido
28	un
29	accidente
30	"
31	,
32	indicó
33	un
34	portavoz
35	de
36	la
37	casa
38	Mattel
39	.
Position	Tokenization	UPOS	Head	Deprel
1	"	PUNCT	3	punct
2	Nos	PRON	3	iobj
3	hizo	VERB	32	ccomp
4	mucha	DET	5	det
5	ilusión	NOUN	3	obj
6	que	SCONJ	11	mark
7	Barbie	PROPN	11	nsubj
8	no	PART	11	advmod
9	sólo	ADV	8	fixed
10	haya	AUX	11	aux
11	servido	VERB	3	csubj
12	de	ADP	13	case
13	diversión	NOUN	11	obj
14	a	ADP	16	case
15	las	DET	16	det
16	niñas	NOUN	13	nmod
17	,	PUNCT	21	punct
18	sino	CCONJ	21	cc
19	que	SCONJ	18	fixed
20	pueda	AUX	21	aux
21	ayudar	VERB	11	conj
22	a	ADP	24	case
23	los	DET	24	det
24	adultos	NOUN	21	obj
25	que	PRON	27	nsubj
26	hayan	AUX	27	aux
27	sufrido	VERB	24	acl
28	un	DET	29	det
29	accidente	NOUN	27	obj
30	"	PUNCT	3	punct
31	,	PUNCT	3	punct
32	indicó	VERB	0	root
33	un	DET	34	det
34	portavoz	NOUN	32	nsubj
35	de	ADP	37	case
36	la	DET	37	det
37	casa	NOUN	34	nmod
38	Mattel	PROPN	37	appos
39	.	PUNCT	32	punct