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 caso les ha tocado a una patrulla de la Guardia Civil, que ha podido tener incluso consecuencias para otros ciudadanos externos a este cuerpo", agregó el presidente navarro, quien subrayó que, en esta ocasión, "afortunadamente" no se han registrado víctimas mortales.
Postion	Tokenization
1	"
2	En
3	este
4	caso
5	les
6	ha
7	tocado
8	a
9	una
10	patrulla
11	de
12	la
13	Guardia
14	Civil
15	,
16	que
17	ha
18	podido
19	tener
20	incluso
21	consecuencias
22	para
23	otros
24	ciudadanos
25	externos
26	a
27	este
28	cuerpo
29	"
30	,
31	agregó
32	el
33	presidente
34	navarro
35	,
36	quien
37	subrayó
38	que
39	,
40	en
41	esta
42	ocasión
43	,
44	"
45	afortunadamente
46	"
47	no
48	se
49	han
50	registrado
51	víctimas
52	mortales
53	.
Position	Tokenization	UPOS	Head	Deprel
1	"	PUNCT	7	punct
2	En	ADP	4	case
3	este	DET	4	det
4	caso	NOUN	7	obl
5	les	PRON	7	obj
6	ha	AUX	7	aux
7	tocado	VERB	31	ccomp
8	a	ADP	10	case
9	una	DET	10	det
10	patrulla	NOUN	7	obj
11	de	ADP	13	case
12	la	DET	13	det
13	Guardia	PROPN	10	nmod
14	Civil	PROPN	13	flat
15	,	PUNCT	19	punct
16	que	PRON	19	nsubj
17	ha	AUX	19	aux
18	podido	AUX	19	aux
19	tener	VERB	7	advcl
20	incluso	ADV	19	advmod
21	consecuencias	NOUN	19	obj
22	para	ADP	24	case
23	otros	DET	24	det
24	ciudadanos	NOUN	21	nmod
25	externos	ADJ	24	amod
26	a	ADP	28	case
27	este	DET	28	det
28	cuerpo	NOUN	25	nmod
29	"	PUNCT	7	punct
30	,	PUNCT	7	punct
31	agregó	VERB	0	root
32	el	DET	33	det
33	presidente	NOUN	31	nsubj
34	navarro	ADJ	33	amod
35	,	PUNCT	37	punct
36	quien	PRON	37	nsubj
37	subrayó	VERB	33	acl
38	que	SCONJ	50	mark
39	,	PUNCT	42	punct
40	en	ADP	42	case
41	esta	DET	42	det
42	ocasión	NOUN	50	obl
43	,	PUNCT	42	punct
44	"	PUNCT	45	punct
45	afortunadamente	ADV	50	advmod
46	"	PUNCT	45	punct
47	no	ADV	50	advmod
48	se	PRON	50	expl:pass
49	han	AUX	50	aux
50	registrado	VERB	37	ccomp
51	víctimas	NOUN	50	nsubj
52	mortales	ADJ	51	amod
53	.	PUNCT	31	punct