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:
A bordo de un helicóptero, para ganar tiempo en las distancias que separan a los pueblos, Don Felipe viajó más tarde a la pequeña localidad de Molinos, en donde su entusiasta alcalde, Mateo Andrés, está empeñado en incorporar al municipio a lo más avanzado de la sociedad de la información.
Postion	Tokenization
1	A
2	bordo
3	de
4	un
5	helicóptero
6	,
7	para
8	ganar
9	tiempo
10	en
11	las
12	distancias
13	que
14	separan
15	a
16	los
17	pueblos
18	,
19	Don
20	Felipe
21	viajó
22	más
23	tarde
24	a
25	la
26	pequeña
27	localidad
28	de
29	Molinos
30	,
31	en
32	donde
33	su
34	entusiasta
35	alcalde
36	,
37	Mateo
38	Andrés
39	,
40	está
41	empeñado
42	en
43	incorporar
44	al
45	municipio
46	a
47	lo
48	más
49	avanzado
50	de
51	la
52	sociedad
53	de
54	la
55	información
56	.
Position	Tokenization	UPOS	Head	Deprel
1	A	ADP	5	case
2	bordo	NOUN	1	fixed
3	de	ADP	1	fixed
4	un	DET	5	det
5	helicóptero	NOUN	21	obl
6	,	PUNCT	8	punct
7	para	ADP	8	mark
8	ganar	VERB	5	acl
9	tiempo	NOUN	8	obj
10	en	ADP	12	case
11	las	DET	12	det
12	distancias	NOUN	8	obl
13	que	PRON	14	nsubj
14	separan	VERB	12	acl
15	a	ADP	17	case
16	los	DET	17	det
17	pueblos	NOUN	14	obj
18	,	PUNCT	5	punct
19	Don	PROPN	21	nsubj
20	Felipe	PROPN	19	flat
21	viajó	VERB	0	root
22	más	ADV	23	advmod
23	tarde	ADV	21	advmod
24	a	ADP	27	case
25	la	DET	27	det
26	pequeña	ADJ	27	amod
27	localidad	NOUN	21	obl
28	de	ADP	29	case
29	Molinos	PROPN	27	nmod
30	,	PUNCT	41	punct
31	en	ADP	32	case
32	donde	PRON	41	obl
33	su	DET	35	det
34	entusiasta	ADJ	35	amod
35	alcalde	NOUN	41	nsubj
36	,	PUNCT	37	punct
37	Mateo	PROPN	35	appos
38	Andrés	PROPN	37	flat
39	,	PUNCT	37	punct
40	está	AUX	41	cop
41	empeñado	ADJ	27	acl
42	en	ADP	43	mark
43	incorporar	VERB	41	xcomp
44	al	ADP	45	case
45	municipio	NOUN	43	obj
46	a	ADP	49	case
47	lo	PRON	49	det
48	más	ADV	49	advmod
49	avanzado	ADJ	43	advmod
50	de	ADP	52	case
51	la	DET	52	det
52	sociedad	NOUN	49	nmod
53	de	ADP	55	case
54	la	DET	55	det
55	información	NOUN	52	nmod
56	.	PUNCT	21	punct