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 Servicio Marítimo de la Guardia Civil de Tarragona ha multado en los últimos 10 días en la Costa Daurada a 30 propietarios de motos acuáticas por diversas infracciones, como no estar matriculadas, carecer de seguro o navegar muy cerca de los bañistas.
Postion	Tokenization
1	El
2	Servicio
3	Marítimo
4	de
5	la
6	Guardia
7	Civil
8	de
9	Tarragona
10	ha
11	multado
12	en
13	los
14	últimos
15	10
16	días
17	en
18	la
19	Costa
20	Daurada
21	a
22	30
23	propietarios
24	de
25	motos
26	acuáticas
27	por
28	diversas
29	infracciones
30	,
31	como
32	no
33	estar
34	matriculadas
35	,
36	carecer
37	de
38	seguro
39	o
40	navegar
41	muy
42	cerca
43	de
44	los
45	bañistas
46	.
Position	Tokenization	UPOS	Head	Deprel
1	El	DET	2	det
2	Servicio	PROPN	11	nsubj
3	Marítimo	PROPN	2	flat
4	de	ADP	6	case
5	la	DET	6	det
6	Guardia	PROPN	2	nmod
7	Civil	PROPN	6	flat
8	de	ADP	9	case
9	Tarragona	PROPN	6	nmod
10	ha	AUX	11	aux
11	multado	VERB	0	root
12	en	ADP	16	case
13	los	DET	15	det
14	últimos	ADJ	15	amod
15	10	NUM	16	nummod
16	días	NOUN	11	obl
17	en	ADP	19	case
18	la	DET	19	det
19	Costa	PROPN	11	obl
20	Daurada	PROPN	19	flat
21	a	ADP	23	case
22	30	NUM	23	nummod
23	propietarios	NOUN	11	obj
24	de	ADP	25	case
25	motos	NOUN	23	nmod
26	acuáticas	ADJ	25	amod
27	por	ADP	29	case
28	diversas	DET	29	det
29	infracciones	NOUN	11	obl
30	,	PUNCT	34	punct
31	como	SCONJ	34	mark
32	no	ADV	34	advmod
33	estar	AUX	34	aux
34	matriculadas	ADJ	29	amod
35	,	PUNCT	36	punct
36	carecer	VERB	34	advcl
37	de	ADP	38	case
38	seguro	NOUN	36	obj
39	o	CCONJ	40	cc
40	navegar	VERB	34	conj
41	muy	ADV	42	advmod
42	cerca	ADV	40	advmod
43	de	ADP	45	case
44	los	DET	45	det
45	bañistas	NOUN	42	obl
46	.	PUNCT	11	punct