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:
La diputada electa transmitió "un abrazo y mi cariño a José María Aznar", a quien definió como "el hombre que ha sabido llevar al PP hasta la victoria", y dio las gracias a la "gente que ha sabido ilusionar y convencer a muchos para que apuesten" por este partido.
Postion	Tokenization
1	La
2	diputada
3	electa
4	transmitió
5	"
6	un
7	abrazo
8	y
9	mi
10	cariño
11	a
12	José
13	María
14	Aznar
15	"
16	,
17	a
18	quien
19	definió
20	como
21	"
22	el
23	hombre
24	que
25	ha
26	sabido
27	llevar
28	al
29	PP
30	hasta
31	la
32	victoria
33	"
34	,
35	y
36	dio
37	las
38	gracias
39	a
40	la
41	"
42	gente
43	que
44	ha
45	sabido
46	ilusionar
47	y
48	convencer
49	a
50	muchos
51	para
52	que
53	apuesten
54	"
55	por
56	este
57	partido
58	.
Position	Tokenization	UPOS	Head	Deprel
1	La	DET	2	det
2	diputada	NOUN	4	nsubj
3	electa	ADJ	2	amod
4	transmitió	VERB	0	root
5	"	PUNCT	7	punct
6	un	DET	7	det
7	abrazo	NOUN	4	obj
8	y	CCONJ	10	cc
9	mi	DET	10	det
10	cariño	NOUN	7	conj
11	a	ADP	12	case
12	José	PROPN	4	obj
13	María	PROPN	12	flat
14	Aznar	PROPN	12	flat
15	"	PUNCT	12	punct
16	,	PUNCT	19	punct
17	a	ADP	18	case
18	quien	PRON	19	obj
19	definió	VERB	12	acl
20	como	SCONJ	23	mark
21	"	PUNCT	23	punct
22	el	DET	23	det
23	hombre	NOUN	19	obl
24	que	PRON	26	nsubj
25	ha	AUX	26	aux
26	sabido	VERB	23	acl
27	llevar	VERB	26	xcomp
28	al	ADP	29	case
29	PP	PROPN	27	obj
30	hasta	ADP	32	case
31	la	DET	32	det
32	victoria	NOUN	27	obl
33	"	PUNCT	23	punct
34	,	PUNCT	19	punct
35	y	CCONJ	36	cc
36	dio	VERB	4	conj
37	las	DET	38	det
38	gracias	NOUN	36	obj
39	a	ADP	42	case
40	la	DET	42	det
41	"	PUNCT	42	punct
42	gente	NOUN	36	obj
43	que	PRON	45	nsubj
44	ha	AUX	45	aux
45	sabido	VERB	42	acl
46	ilusionar	VERB	45	xcomp
47	y	CCONJ	48	cc
48	convencer	VERB	46	conj
49	a	ADP	50	case
50	muchos	PRON	46	obj
51	para	ADP	53	mark
52	que	SCONJ	53	mark
53	apuesten	VERB	46	advcl
54	"	PUNCT	53	punct
55	por	ADP	57	case
56	este	DET	57	det
57	partido	NOUN	53	obj
58	.	PUNCT	4	punct