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:
En la bolsa española, la publicación de los datos estadounidenses benefició principalmente a los dos grandes bancos españoles, BBVA y BSCH, que cerraron con alzas del 2,38% y 1,55%, respectivamente.
Postion	Tokenization
1	En
2	la
3	bolsa
4	española
5	,
6	la
7	publicación
8	de
9	los
10	datos
11	estadounidenses
12	benefició
13	principalmente
14	a
15	los
16	dos
17	grandes
18	bancos
19	españoles
20	,
21	BBVA
22	y
23	BSCH
24	,
25	que
26	cerraron
27	con
28	alzas
29	del
30	2,38%
31	y
32	1,55%
33	,
34	respectivamente
35	.
Position	Tokenization	UPOS	Head	Deprel
1	En	ADP	3	case
2	la	DET	3	det
3	bolsa	NOUN	12	obl
4	española	ADJ	3	amod
5	,	PUNCT	3	punct
6	la	DET	7	det
7	publicación	NOUN	12	nsubj
8	de	ADP	10	case
9	los	DET	10	det
10	datos	NOUN	7	nmod
11	estadounidenses	ADJ	10	amod
12	benefició	VERB	0	root
13	principalmente	ADV	12	obj
14	a	ADP	13	case
15	los	DET	18	det
16	dos	NUM	15	nummod
17	grandes	ADJ	18	amod
18	bancos	NOUN	13	nmod
19	españoles	ADJ	18	amod
20	,	PUNCT	21	punct
21	BBVA	PROPN	18	appos
22	y	CCONJ	23	cc
23	BSCH	PROPN	21	conj
24	,	PUNCT	26	punct
25	que	PRON	26	nsubj
26	cerraron	VERB	18	acl
27	con	ADP	28	case
28	alzas	NOUN	26	obl
29	del	ADP	30	case
30	2,38%	SYM	28	nmod
31	y	CCONJ	32	cc
32	1,55%	SYM	30	conj
33	,	PUNCT	34	punct
34	respectivamente	ADV	30	advmod
35	.	PUNCT	12	punct