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 este sentido, advirtió de que quiere "más ambiciones" para España a través de objetivos concretos y que no le interesa si va a haber una campaña electoral "sucia", porque sólo será así "por aquellos que sólo saben hacer política sucia".
Postion	Tokenization
1	En
2	este
3	sentido
4	,
5	advirtió
6	de
7	que
8	quiere
9	"
10	más
11	ambiciones
12	"
13	para
14	España
15	a
16	través
17	de
18	objetivos
19	concretos
20	y
21	que
22	no
23	le
24	interesa
25	si
26	va
27	a
28	haber
29	una
30	campaña
31	electoral
32	"
33	sucia
34	"
35	,
36	porque
37	sólo
38	será
39	así
40	"
41	por
42	aquellos
43	que
44	sólo
45	saben
46	hacer
47	política
48	sucia
49	"
50	.
Position	Tokenization	UPOS	Head	Deprel
1	En	ADP	3	case
2	este	DET	3	det
3	sentido	NOUN	5	obl
4	,	PUNCT	3	punct
5	advirtió	VERB	0	root
6	de	ADP	8	mark
7	que	SCONJ	8	mark
8	quiere	VERB	5	ccomp
9	"	PUNCT	11	punct
10	más	ADV	11	advmod
11	ambiciones	NOUN	8	obj
12	"	PUNCT	11	punct
13	para	ADP	14	case
14	España	PROPN	8	obl
15	a	ADP	18	case
16	través	NOUN	15	fixed
17	de	ADP	15	fixed
18	objetivos	NOUN	8	obl
19	concretos	ADJ	18	amod
20	y	CCONJ	24	cc
21	que	SCONJ	24	mark
22	no	ADV	24	advmod
23	le	PRON	24	obj
24	interesa	VERB	8	conj
25	si	SCONJ	28	mark
26	va	AUX	24	aux
27	a	ADP	28	mark
28	haber	AUX	24	csubj
29	una	DET	30	det
30	campaña	NOUN	28	obj
31	electoral	ADJ	30	amod
32	"	PUNCT	33	punct
33	sucia	ADJ	30	amod
34	"	PUNCT	33	punct
35	,	PUNCT	39	punct
36	porque	SCONJ	39	mark
37	sólo	ADV	39	advmod
38	será	AUX	39	cop
39	así	ADV	28	advcl
40	"	PUNCT	42	punct
41	por	ADP	42	case
42	aquellos	PRON	39	obl
43	que	PRON	45	nsubj
44	sólo	ADV	45	advmod
45	saben	VERB	42	acl
46	hacer	VERB	45	xcomp
47	política	NOUN	46	obj
48	sucia	ADJ	47	amod
49	"	PUNCT	42	punct
50	.	PUNCT	5	punct