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:
Precisó que el mayor número de indocumentados deportados en la zona sureste se realiza a través de los puntos fronterizos de Chiapas, en las ciudades de Talismán, Hidalgo y Cuauhtémoc.
Postion	Tokenization
1	Precisó
2	que
3	el
4	mayor
5	número
6	de
7	indocumentados
8	deportados
9	en
10	la
11	zona
12	sureste
13	se
14	realiza
15	a
16	través
17	de
18	los
19	puntos
20	fronterizos
21	de
22	Chiapas
23	,
24	en
25	las
26	ciudades
27	de
28	Talismán
29	,
30	Hidalgo
31	y
32	Cuauhtémoc
33	.
Position	Tokenization	UPOS	Head	Deprel
1	Precisó	VERB	0	root
2	que	SCONJ	14	mark
3	el	DET	5	det
4	mayor	ADJ	5	amod
5	número	NOUN	14	nsubj
6	de	ADP	7	case
7	indocumentados	NOUN	5	nmod
8	deportados	ADJ	7	amod
9	en	ADP	11	case
10	la	DET	11	det
11	zona	NOUN	8	obl
12	sureste	ADJ	11	amod
13	se	PRON	14	expl:pass
14	realiza	VERB	1	ccomp
15	a	ADP	19	case
16	través	NOUN	15	fixed
17	de	ADP	15	fixed
18	los	DET	19	det
19	puntos	NOUN	14	obl
20	fronterizos	ADJ	19	amod
21	de	ADP	22	case
22	Chiapas	PROPN	19	nmod
23	,	PUNCT	26	punct
24	en	ADP	26	case
25	las	DET	26	det
26	ciudades	NOUN	19	nmod
27	de	ADP	28	case
28	Talismán	PROPN	26	nmod
29	,	PUNCT	30	punct
30	Hidalgo	PROPN	28	conj
31	y	CCONJ	32	cc
32	Cuauhtémoc	PROPN	28	conj
33	.	PUNCT	1	punct