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:
"Parece una tarea de titanes, en la que la ventaja es que Michigan no es Carolina del Sur, pero McCain sólo va a tener tres días por delante, donde Bush tuvo 18", dijo Dante Chinni, un comentarista del diario "The Christian Science Monitor" en un programa de debates.
Postion	Tokenization
1	"
2	Parece
3	una
4	tarea
5	de
6	titanes
7	,
8	en
9	la
10	que
11	la
12	ventaja
13	es
14	que
15	Michigan
16	no
17	es
18	Carolina
19	del
20	Sur
21	,
22	pero
23	McCain
24	sólo
25	va
26	a
27	tener
28	tres
29	días
30	por
31	delante
32	,
33	donde
34	Bush
35	tuvo
36	18
37	"
38	,
39	dijo
40	Dante
41	Chinni
42	,
43	un
44	comentarista
45	del
46	diario
47	"
48	The
49	Christian
50	Science
51	Monitor
52	"
53	en
54	un
55	programa
56	de
57	debates
58	.
Position	Tokenization	UPOS	Head	Deprel
1	"	PUNCT	2	punct
2	Parece	VERB	39	ccomp
3	una	DET	4	det
4	tarea	NOUN	2	xcomp
5	de	ADP	6	case
6	titanes	NOUN	4	nmod
7	,	PUNCT	13	punct
8	en	ADP	10	case
9	la	DET	10	det
10	que	PRON	13	obl
11	la	DET	12	det
12	ventaja	NOUN	13	nsubj
13	es	AUX	4	acl
14	que	SCONJ	18	mark
15	Michigan	PROPN	18	nsubj
16	no	ADV	18	advmod
17	es	AUX	18	cop
18	Carolina	PROPN	13	ccomp
19	del	ADP	20	case
20	Sur	PROPN	18	flat
21	,	PUNCT	27	punct
22	pero	CCONJ	27	cc
23	McCain	PROPN	27	nsubj
24	sólo	ADV	27	advmod
25	va	AUX	27	aux
26	a	ADP	27	mark
27	tener	VERB	4	conj
28	tres	NUM	29	nummod
29	días	NOUN	27	obj
30	por	ADP	31	case
31	delante	ADV	29	advmod
32	,	PUNCT	35	punct
33	donde	ADV	35	advmod
34	Bush	PROPN	35	nsubj
35	tuvo	VERB	27	advcl
36	18	NUM	35	obj
37	"	PUNCT	2	punct
38	,	PUNCT	2	punct
39	dijo	VERB	0	root
40	Dante	PROPN	39	nsubj
41	Chinni	PROPN	40	flat
42	,	PUNCT	44	punct
43	un	DET	44	det
44	comentarista	NOUN	40	appos
45	del	ADP	46	case
46	diario	NOUN	44	nmod
47	"	PUNCT	48	punct
48	The	PROPN	46	appos
49	Christian	PROPN	48	flat
50	Science	PROPN	48	flat
51	Monitor	PROPN	48	flat
52	"	PUNCT	48	punct
53	en	ADP	55	case
54	un	DET	55	det
55	programa	NOUN	39	obl
56	de	ADP	57	case
57	debates	NOUN	55	nmod
58	.	PUNCT	39	punct