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:
Es una persona muy segura de sí misma que confía mucho en mí ", explicó a Efe Lamela, que este año seguirá entrenándose en las instalaciones ovetenses de San Lázaro, pero ha cambiado su matrícula universitaria y en lugar de estudiar informática en Gijón, lo hará en Oviedo.
Postion	Tokenization
1	Es
2	una
3	persona
4	muy
5	segura
6	de
7	sí
8	misma
9	que
10	confía
11	mucho
12	en
13	mí
14	"
15	,
16	explicó
17	a
18	Efe
19	Lamela
20	,
21	que
22	este
23	año
24	seguirá
25	entrenándose
26	entrenando
27	se
28	en
29	las
30	instalaciones
31	ovetenses
32	de
33	San
34	Lázaro
35	,
36	pero
37	ha
38	cambiado
39	su
40	matrícula
41	universitaria
42	y
43	en
44	lugar
45	de
46	estudiar
47	informática
48	en
49	Gijón
50	,
51	lo
52	hará
53	en
54	Oviedo
55	.
Position	Tokenization	UPOS	Head	Deprel
1	Es	AUX	3	cop
2	una	DET	3	det
3	persona	NOUN	16	ccomp
4	muy	ADV	5	advmod
5	segura	ADJ	3	amod
6	de	ADP	7	case
7	sí	PRON	5	nmod
8	misma	PRON	7	appos
9	que	PRON	10	nsubj
10	confía	VERB	3	acl
11	mucho	ADV	10	advmod
12	en	ADP	13	case
13	mí	PRON	10	obj
14	"	PUNCT	3	punct
15	,	PUNCT	3	punct
16	explicó	VERB	0	root
17	a	ADP	18	case
18	Efe	PROPN	16	iobj
19	Lamela	PROPN	16	nsubj
20	,	PUNCT	24	punct
21	que	PRON	24	nsubj
22	este	DET	23	det
23	año	NOUN	24	obl
24	seguirá	VERB	19	acl
25	entrenándose	_	None	_
26	entrenando	VERB	24	xcomp
27	se	PRON	25	expl:pv
28	en	ADP	29	case
29	las	DET	29	det
30	instalaciones	NOUN	24	obl
31	ovetenses	ADJ	29	amod
32	de	ADP	32	case
33	San	PROPN	29	nmod
34	Lázaro	PROPN	32	flat
35	,	PUNCT	37	punct
36	pero	CCONJ	37	cc
37	ha	AUX	37	aux
38	cambiado	VERB	25	conj
39	su	DET	39	det
40	matrícula	NOUN	37	obj
41	universitaria	ADJ	39	amod
42	y	CCONJ	51	cc
43	en	ADP	45	mark
44	lugar	NOUN	42	fixed
45	de	ADP	42	fixed
46	estudiar	VERB	51	advcl
47	informática	NOUN	45	obj
48	en	ADP	48	case
49	Gijón	PROPN	45	obl
50	,	PUNCT	45	punct
51	lo	PRON	51	obj
52	hará	VERB	37	conj
53	en	ADP	53	case
54	Oviedo	PROPN	51	obl
55	.	PUNCT	16	punct