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:
"Puedo asegurar que él (Segura) mintió, por lo menos a mí", dijo Vázquez Raña al responder a la decisión del atleta de someterse al detector de mentiras en una cadena de televisión por cable para aclarar que ignoraba su descalificación, que ha generado una gran polémica en México.
Postion	Tokenization
1	"
2	Puedo
3	asegurar
4	que
5	él
6	(
7	Segura
8	)
9	mintió
10	,
11	por
12	lo
13	menos
14	a
15	mí
16	"
17	,
18	dijo
19	Vázquez
20	Raña
21	al
22	responder
23	a
24	la
25	decisión
26	del
27	atleta
28	de
29	someterse
30	someter
31	se
32	al
33	detector
34	de
35	mentiras
36	en
37	una
38	cadena
39	de
40	televisión
41	por
42	cable
43	para
44	aclarar
45	que
46	ignoraba
47	su
48	descalificación
49	,
50	que
51	ha
52	generado
53	una
54	gran
55	polémica
56	en
57	México
58	.
Position	Tokenization	UPOS	Head	Deprel
1	"	PUNCT	3	punct
2	Puedo	AUX	3	aux
3	asegurar	VERB	18	xcomp
4	que	SCONJ	9	mark
5	él	PRON	9	nsubj
6	(	PUNCT	7	punct
7	Segura	PROPN	5	appos
8	)	PUNCT	7	punct
9	mintió	VERB	3	ccomp
10	,	PUNCT	11	punct
11	por	ADP	9	obj
12	lo	PRON	11	fixed
13	menos	ADV	11	fixed
14	a	ADP	11	case
15	mí	PRON	11	nmod
16	"	PUNCT	3	punct
17	,	PUNCT	3	punct
18	dijo	VERB	0	root
19	Vázquez	PROPN	18	nsubj
20	Raña	PROPN	19	flat
21	al	ADP	22	mark
22	responder	VERB	18	advcl
23	a	ADP	25	case
24	la	DET	25	det
25	decisión	NOUN	22	obj
26	del	ADP	27	case
27	atleta	NOUN	25	nmod
28	de	ADP	29	mark
29	someterse	_	None	_
30	someter	VERB	25	acl
31	se	PRON	29	obj
32	al	ADP	32	case
33	detector	NOUN	29	obj
34	de	ADP	34	case
35	mentiras	NOUN	32	nmod
36	en	ADP	37	case
37	una	DET	37	det
38	cadena	NOUN	29	obl
39	de	ADP	39	case
40	televisión	NOUN	37	nmod
41	por	ADP	41	case
42	cable	NOUN	37	nmod
43	para	ADP	43	mark
44	aclarar	VERB	29	advcl
45	que	SCONJ	45	mark
46	ignoraba	VERB	43	ccomp
47	su	DET	47	det
48	descalificación	NOUN	45	obj
49	,	PUNCT	51	punct
50	que	PRON	51	nsubj
51	ha	AUX	51	aux
52	generado	VERB	47	acl
53	una	DET	54	det
54	gran	ADJ	54	amod
55	polémica	NOUN	51	obj
56	en	ADP	56	case
57	México	PROPN	51	obl
58	.	PUNCT	18	punct