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 euro representa la respuesta europea para conseguir el objetivo de un mayor nivel de empleo y bienestar de nuestros ciudadanos. El euro es la mejor base para crear empleo", insistió.
Postion	Tokenization
1	"
2	El
3	euro
4	representa
5	la
6	respuesta
7	europea
8	para
9	conseguir
10	el
11	objetivo
12	de
13	un
14	mayor
15	nivel
16	de
17	empleo
18	y
19	bienestar
20	de
21	nuestros
22	ciudadanos
23	.
24	El
25	euro
26	es
27	la
28	mejor
29	base
30	para
31	crear
32	empleo
33	"
34	,
35	insistió
36	.
Position	Tokenization	UPOS	Head	Deprel
1	"	PUNCT	4	punct
2	El	DET	3	det
3	euro	NOUN	4	nsubj
4	representa	VERB	35	ccomp
5	la	DET	6	det
6	respuesta	NOUN	4	obj
7	europea	ADJ	6	amod
8	para	ADP	9	mark
9	conseguir	VERB	6	acl
10	el	DET	11	det
11	objetivo	NOUN	9	obj
12	de	ADP	15	case
13	un	DET	15	det
14	mayor	ADJ	15	amod
15	nivel	NOUN	11	nmod
16	de	ADP	17	case
17	empleo	NOUN	15	nmod
18	y	CCONJ	19	cc
19	bienestar	NOUN	17	conj
20	de	ADP	22	case
21	nuestros	DET	22	det
22	ciudadanos	NOUN	15	nmod
23	.	PUNCT	4	punct
24	El	DET	25	det
25	euro	NOUN	29	nsubj
26	es	AUX	29	cop
27	la	DET	29	det
28	mejor	ADJ	29	amod
29	base	NOUN	4	advcl
30	para	ADP	31	mark
31	crear	VERB	29	acl
32	empleo	NOUN	31	obj
33	"	PUNCT	4	punct
34	,	PUNCT	4	punct
35	insistió	VERB	0	root
36	.	PUNCT	35	punct