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 señora Aguirre encarna de repente todo ese afán marujón y exterminador que le ha entrado a la derecha gubernamental, paragubernamental, municipal, empresarial y paraempresarial por castigar, represaliar, asfixiar, borrar las huellas, los moretones, las llagas de la huelga.
Postion	Tokenization
1	La
2	señora
3	Aguirre
4	encarna
5	de
6	repente
7	todo
8	ese
9	afán
10	marujón
11	y
12	exterminador
13	que
14	le
15	ha
16	entrado
17	a
18	la
19	derecha
20	gubernamental
21	,
22	paragubernamental
23	,
24	municipal
25	,
26	empresarial
27	y
28	paraempresarial
29	por
30	castigar
31	,
32	represaliar
33	,
34	asfixiar
35	,
36	borrar
37	las
38	huellas
39	,
40	los
41	moretones
42	,
43	las
44	llagas
45	de
46	la
47	huelga
48	.
Position	Tokenization	UPOS	Head	Deprel
1	La	DET	2	det
2	señora	NOUN	4	nsubj
3	Aguirre	PROPN	2	appos
4	encarna	VERB	0	root
5	de	ADP	4	advmod
6	repente	NOUN	5	fixed
7	todo	DET	8	det
8	ese	DET	9	det
9	afán	NOUN	4	obj
10	marujón	ADJ	9	amod
11	y	CCONJ	12	cc
12	exterminador	ADJ	10	conj
13	que	PRON	16	nsubj
14	le	PRON	16	obj
15	ha	AUX	16	aux
16	entrado	VERB	9	acl
17	a	ADP	19	case
18	la	DET	19	det
19	derecha	NOUN	16	obj
20	gubernamental	ADJ	19	amod
21	,	PUNCT	22	punct
22	paragubernamental	ADJ	20	amod
23	,	PUNCT	24	punct
24	municipal	ADJ	20	amod
25	,	PUNCT	26	punct
26	empresarial	ADJ	20	amod
27	y	CCONJ	28	cc
28	paraempresarial	ADJ	20	conj
29	por	ADP	30	mark
30	castigar	VERB	9	acl
31	,	PUNCT	30	punct
32	represaliar	VERB	30	advcl
33	,	PUNCT	30	punct
34	asfixiar	VERB	30	advcl
35	,	PUNCT	30	punct
36	borrar	VERB	30	advcl
37	las	DET	38	det
38	huellas	NOUN	36	obj
39	,	PUNCT	38	punct
40	los	DET	41	det
41	moretones	NOUN	38	appos
42	,	PUNCT	38	punct
43	las	DET	44	det
44	llagas	NOUN	38	appos
45	de	ADP	47	case
46	la	DET	47	det
47	huelga	NOUN	38	nmod
48	.	PUNCT	4	punct